Dissertations / Theses: 'AI ChatBot'

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Aljadri, Sinan. "Chatbot : A qualitative study of users' experience of Chatbots." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105434.

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The aim of the present study has been to examine users' experience of Chatbot from a business perspective and a consumer perspective. The study has also focused on highlighting what limitations a Chatbot can have and possible improvements for future development. The study is based on a qualitative research method with semi-structured interviews that have been analyzed on the basis of a thematic analysis. The results of the interview material have been analyzed based on previous research and various theoretical perspectives such as Artificial Intelligence (AI), Natural Language Processing (NLP). The results of the study have shown that the experience of Chatbot can differ between businesses that offer Chatbot, which are more positive and consumers who use it as customer service. Limitations and suggestions for improvements around Chatbotar are also a consistent result of the study.
Den föreliggande studie har haft som syfte att undersöka användarnas upplevelse av Chatbot utifrån verksamhetsperspektiv och konsumentperspektiv. Studien har också fokuserat på att lyfta fram vilka begränsningar en Chatbot kan ha och eventuella förbättringar för framtida utvecklingen. Studien är baserad på en kvalitativ forskningsmetod med semistrukturerade intervjuer som har analyserats utifrån en tematisk analys. Resultatet av intervjumaterialet har analyserat utifrån tidigare forskning och olika teoretiska perspektiv som Artificial Intelligence (AI), Natural Language Processing (NLP). Resultatet av studien har visat att upplevelsen av Chatbot kan skilja sig mellan verksamheter som erbjuder Chatbot, som är mer positiva och konsumenter som använder det som kundtjänst. Begränsningar och förslag på förbättringar kring Chatbotar är också ett genomgående resultat i studien.

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Jusko, Ján. "Chatbot pro Smart Cities." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403204.

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The aim of this work is to simplify access to information for citizens of the city of Brno and at the same time to innovate the way of communication between the citizen and his city. The problem is solved by creating a conversational agent - chatbot Kroko. Using artificial intelligence and a Czech language analyzer, the agent is able to understand and respond to a certain set of textual, natural language queries. The agent is available on the Messenger platform and has a knowledge base that includes data provided by the city council. After conducting an extensive user testing on a total of 76 citizens of the city, it turned out that up to 97\% of respondents like the idea of a city-oriented chatbot and can imagine using it regularly. The main finding of this work is that the general public can easily adopt and effectively use a chatbot. The results of this work motivate further development of practical applications of conversational agents.

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Eklund, Joakim, and Fred Isaksson. "Identifying & Evaluating SystemComponents for Cognitive Trustin AI-Automated Service Encounters : Trusting a Study- & Vocational Chatbot." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-386044.

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The intensifying idea that AI soon will be a part of our everyday life allows for dreams about the complex relationship we one day could have with non-biological social intelligence. However, establishing societal and individual acceptance of AI-powered autonomy in disciplines built upon to the reliance to human competence raises a number of pressing challenges. One of them being, what system components will engender respectively counteract cognitive trust in socially oriented AI-automated processes? This masters thesis tackles the seemingly ambiguous concept of trust in automation by identifying and evaluating system components that affect trust in a confined and contextualised setting. Practically, we design, construct and test an AI-powered chatbot, Ava, that contains socially oriented questions and feedback about study- and vocational guidance. Through a comparative study of different system versions, including both quantitative and qualitative data, we contribute to the framework for identifying and evaluating human trust in AI-Automated service encounters. We show how targeted alterations to design choices constituting the system components transparency, unbiasses and system performance, identified to affect trust, has consequences on the perception of the cognitive trust concepts integrity, benevolence and ability. Our results display a way of conduct for practitioners looking to prioritise and develop trustworthy autonomy. More specifically, we account for how cognitive trust is decreased when system opacity is increased. Moreover, we display even more concerning effects on trust due to micking contextual bias in the conversation agent.

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Gligorijevic, Ilic Nemanja. "Utveckling av en FAQ chatbot - för frågor om ett program på ett universitet." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85197.

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The implementation of chatbots and service services is becoming more common. The reason for this is that they are constantly available to answer questions, no matter what time it is. To make one chatbot is not just to write questions and specific answers. Communicating with one chatbot should, as much as possible, look like communicating with another human. The purpose of this report is to create a chatbot that will be used at Luleå university of technology and that will answer questions about system science. Furthermore, the goal is to investigate which design principles should be implemented, their possible concretization, when making chatbots, and possibly coming to new principles. The method used to make the chatbot is Design Science Research Methodology (DSRM). DSRM focuses on solving the problem by creating an IT artifact, which in this case is a chatbot. The result of this work is a created chatbot and design principles that were implemented during the development process.

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Svenningsson, Nina. "What’s up AI?! : En undersökning kring människoliknande beteende hos chatbotar och dess påverkan på användarupplevelsen." Thesis, Högskolan Kristianstad, Fakulteten för ekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-19854.

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Artificiell intelligens (AI) sprider sig genom samhället och används mer och mer inom flera olika områden. Chatbotar är en populär form av social AI som använder sig av naturligt språk för att kommunicera med användare. Det finns olika åsikter kring huruvida en chatbot ska prata och bete sig människolikt eller inte. Den ena sidan argumenterar att chatbotar ska fortsätta utvecklas för att kunna simulera mänskligt beteende och intelligens, å andra sidan argumenteras att chatbotar ska vara tydliga med att de är maskiner och att det även kan vara positivt för användarupplevelsen om chatbotar inte är alltför människolika. Dessutom finns det teorier om att ett beteende som är för människolikt kan skapa obehag hos användaren. Detta examensarbete syftar till att undersöka den diskrepans som har observerats i resultaten från vetenskapliga studier för att ge indikationer på vilka faktorer som bidrar till en positiv användarupplevelse i interaktionen med chatbotar i förhållande till hur människolika de uppfattas. Resultatet visar på att det finns en stor bredd i användares preferenser för hur en chatbot bör bete sig vilket gör det svårt att nämna specifika människoliknande faktorer som är tilltalande för en större grupp användare. Om man idag vill designa en chatbot som tilltalar så många användare som möjligt bör man ge den en officiell/formell ton samt låta den svara kort, koncist och med sofistikerade ordval och välkonstruerade meningar. För att gå vidare rekommenderas bland annat att undersöka hur chatbotar kan anpassa sitt beteende efter olika användare för att skapa en positiv användarupplevelse.

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Andersson, Ludvig, and Erik Felin. "AI inom vårdrådgivning : En attitydanalys på 1177 Vårdguidens sjuksköterskor." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-376660.

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Artificiell intelligens (AI) är en teknik som blir allt vanligare inom en rad områden, inte minst i syfte att effektivisera. I Sverige har kritik riktats mot vårdbranschen och de långa vårdköer som tynger den. Undersökningen syftar till att undersöka AI:s potential inom vårdbranschen i allmänhet och 1177 Vårdguiden i synnerhet. Genom en attitydanalys baserad på fyra intervjuer med 1177 Vårdguidens sjuksköterskor, kommer undersökningen fram till att AI har en viss potential när det gäller administrativa ärenden. Vad gäller vårdärenden är attityden inför AI mer negativ och dess potential tros inte vara tillräcklig för att ersätta den mänskliga faktorn.
Artificial intelligence is a technology that is becoming increasingly common in a number of fields, not least in order to streamline. In Sweden criticism has been directed at the healthcare industry and the long queues that overburden it. The study aims to investigate AI's potential in the healthcare industry in general and 1177 Vårdguiden in particular. Through an attitude analysis based on four interviews with 1177 Vårdguiden nurses, the survey concludes that AI has some potential in terms of administrative matters. When it comes to care-related cases, the attitude towards AI is more negative and its potential is not believed to be sufficient in order to replace the human factor.

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Kero, Chanelle, and Veronica Törnblom. "Utveckling av en chatbots dialog för implementation i en webbaserad kundtjänst." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-69046.

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Automatisering av kundtjänster genom implementering av chatbotar blir allt vanligare för att kunna erbjuda kunder en mer tillgänglig och effektiv service. Vid implementering av chatbotar i kundtjänster lämnas den mänskliga kontrollen och kundens upplevelse delvis över till ett digitalt system, vilket ställer krav på utformning av chatbotars dialoger. Syftet med arbetet är att ta fram en artefakt i form av en chatbot och utveckla dess dialog för en framtida implementation i en kundtjänst. Arbetet ämnar att ta fram designprinciper för utformning och utveckling av chatbotar och deras dialoger i en kundtjänstmiljö. Den forskningsmetod som tillämpades vid utvecklingen av artefakten var Design Science Research Methodology (DSRM). En litteraturstudie genomfördes och data samlades in genom möten samt en intervju med det företag som varit uppdragsgivare till arbetet. Arbetet resulterade i en demosida innehållande en chatbot, samt en sida för administratörer där de har en översikt av chatbotens genomförda interaktioner. Tre designprinciper togs även fram för utveckling av chatbotars dialog inom kundtjänst, vilka blev arbetets bidrag. De slutsatser som identifierades var att en chatbot bör kontrollera att användaren fått svar på sitt kundtjänstärende, en chatbot bör erbjuda mänsklig service vid missförstånd, en chatbot kan inte ersätta mänsklig service fullt ut samt att en chatbot bör ha en strukturerad datainsamling av genomförda interaktioner för att kunna utveckla och förbättra chatbotens dialog.
Automation of customer service through implementation of chatbots is becoming increasingly common in order to provide customers with a more accessible and efficient service. When implementing chatbots in customer services, human control and the customer experience are partially shifted to a digital system, which puts requirement on the chatbot’s dialogue. The purpose of this report is to develop an artifact for a client. The artifact is a web page containing a chatbot. The report aims to develop design principles for development of chatbots and their dialogues in a customer service. The research method used in the development of the artifact was Design Science Research Methodology (DSRM). A literature study was conducted, and data was collected through meetings and an interview with the client. The report resulted in a demo page containing a chatbot and a page for administrators with an overview of saved chats. Three design principles were also formulated for developing chatbots in customer service, which is the contribution of the report. The conclusions identified were that a chatbot should check that the user got the correct answer, a chatbot should offer human service in case of misunderstanding, a chatbot cannot fully replace human service and a chatbot should have a structured data collection of completed interactions for developing and improvement of the chatbot’s dialogue.

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Wärmegård, Erik. "Intelligent chatbot assistant: A study of integration with VOIP and Artificial Intelligence." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42693.

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Development and research on Artificial Intelligence have increased during recent years, and the field of medicine is not excluded as a target audience for this top modern technology. Despite new research and tools in favor of medical care, the staff is still under heavy workloads. The goal of this thesis is to analyze and propose the possibility of a chatbot that aims to ease the pressure on the medical staff. To provide a guarantee that patients are being monitored. With Artificial Intelligence, VOIP, Natural Language Processing, and web development, this chatbot can communicate with a patient, which will act as an assistant tool that conducts preparatory work for the medical staff. The system of the chatbot is integrated through a web application where the administrator can initiate call and store clients onto the database. To ascertain that the system operates in real-time, several tests have been carried out to tests concerning the latency between subsystems and the quality of service.
I utvecklingen av intelligenta system har sjukvården etablerat sig som en stor målgrupp. Trots avancerade tekniker så är sjukvården fortfarande under tung belastning. Målet för detta examensarbete är att undersöka möjligheten av en chatbot vars syfte är att lätta på arbetsbelastningen hos sjukvårdspersonalen och samtidigt erbjuda en garanti för att patienter får den tillsyn och återkoppling de behöver. Med hjälp av Artificiell Intelligens, VOIP, Natural Language Processing och webbutveckling kan denna chatbot kommunicera med patienten. Chatboten agerar som ett assisterande verktyg som står för ett förarbete i beslutstagandet för sjukvårdspersonal. Ett systemsom inte bara ger praktisk nytta utan också ett främjande av den utveckling som Artificiell Intelligens gör inom sjukvården. Systemet administreras genom en hemsida som kopplar samman de flera olika komponenterna. Här kan en administratör initiera samtal och spara klienter som ska ringas till databasen. För att kunna fastställa att systemet opererar i realtid har görs flertalet prestandatester avseende både tidsfördröjningar och samtalskvalité.

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Lilja, Adam, and Max Kihlborg. "Important criteria when choosing a conversational AI platform for enterprises." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280896.

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This paper evaluates and analyzes three conversational AI-platforms; Dialogflow (Google), Watson Assistant (IBM) and Teneo (Artificial Solutions) on how they perform based on a set of criteria; pricing model, ease-of-use, efficiency, experience working in the software and what results to expect from each platform. The main focus was to investigate the platforms in order to acquire an understanding of which platform would best be suited for enterprises. The platforms were compared by performing a variety of tasks aiming to answer these questions. The technical research was combined with an analysis of each company’s pricing model and strategy to get an understanding of how they target their products on the market. This study concludes that different softwares may be suitable for different settings depending on the size of an enterprise and the demand for complex solutions. Overall, Teneo outperformed its competitors in these tests and seems to be the most scalable solution with the ability to create both simple and complicated solutions. It was more demanding to get started in comparison with the other platforms, but became more efficient as time progressed. Some findings include that Dialogflow and Watson Assistant lacked capabilities when faced with complex and complicated tasks. From a pricing strategy point of view, the companies are similar in their approach but Artificial Solutions and IBM has more flexible methods while Google has a fixed pricing strategy. Combining the pricing strategy and technical analysis this implicates that Teneo would be a better choice for larger enterprises while Watson Assistant and Dialogflow may be more suitable for smaller ones.
Det här arbetet evaluerar och analyserar tre konversationella AI-plattformar; Dialogflow (Google), Watson Assistant (IBM) och Teneo (Artificial Solutions) utifrån hur de presterar baserat på ett antal kriterier; prismodell, enkel användning, effektivitet, upplevelse att arbeta i programvaran och vilka resultat man förväntar sig från varje plattform. Huvudsakligt fokus var att undersöka plattformarna för att få en uppfattning om vilken plattform som skulle passa bäst för företag. Plattformarna jämfördes genom att utföra en mängd olika uppgifter som syftade till att besvara dessa frågor. Den tekniska forskningen kombinerades med en analys av varje företags prismodell och prisstrategi för att få en uppfattning av hur de riktar sina produkter på marknaden. Denna studie drar slutsatsen att olika programvaror kan vara lämpliga för olika sammanhang beroende på ett företags storlek och dess efterfrågan på komplexa lösningar. Sammantaget överträffade Teneo sina konkurrenter i dessa tester och verkar vara den mest skalbara lösningen med förmågan att skapa både enkla och komplicerade lösningar. Det var mer krävande att komma igång i jämförelse med de andra plattformarna, men det blev mer effektivt med tiden. Vissa fynd inkluderar att Dialogflow och Watson Assistant saknade kapacitet när de mötte komplexa och komplicerade uppgifter. Från en prissättningsstrategisk synvinkel är företagen liknande i sin metod men Artificial Solutions och IBM har mer flexibla metoder medan Google har en fast prissättningstrategi. Genom att kombinera prisstrategi och teknisk analys innebär detta att Teneo skulle vara ett bättre val för större företag medan Watson Assistant och Dialogflow kan vara mer lämpade för mindre.

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Castellucci, Matteo. "Applicazione di tecniche AI per la progettazione di un sistema a supporto del paziente iperteso." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21654/.

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In questa tesi si è cercato di trovare le soluzioni più efficaci a supporto delle questioni legate all'ipertensione di seguito descritte attraverso l'uso di tecniche riguardanti l'intelligenza artificiale e l'Internet of Things. Uno tra i compiti dei medici che si occupano di curare i malati di ipertensione è quello di elaborare protocolli per quanto riguarda la prevenzione e la cura di questa malattia, i quali vengono periodicamente aggiornati. Per supportare ciò, il primo progetto sviluppato è consistito in un'analisi dei dati sul dataset ottenuto a partire dall'elaborazione delle risposte date ai questionari che sono stati distribuiti durante la Giornata Mondiale dell'Ipertensione. A partire da questo, si è cercato di evidenziare la classe di persone che con più probabilità sono malate di ipertensione in modo tale che le linee guida aggiornate si concentrino maggiormente su costoro. La seconda questione affrontata è che non sempre le cure che vengono prescritte sono efficaci, talvolta a causa del medico, talvolta a causa del paziente. Si rende perciò necessario fornire ai pazienti degli strumenti che li aiutino direttamente nella cura della loro malattia. Devono avere anche lo scopo di aiutare il medico nel suo lavoro di monitoraggio periodico delle condizioni di salute del paziente, perché possa avere realmente il polso della situazione. Per fare questo, il secondo progetto ha riguardato lo sviluppo di un chatbot disponibile sulla piattaforma di messaggistica istantanea Telegram ad uso dei malati di ipertensione. Questo assistente virtuale permette loro di registrare le misurazioni di pressione che settimanalmente devono effettuare e ricorda loro di farlo quando passa troppo tempo dall'ultima misurazione. Il sistema permette inoltre di visualizzare medie e grafici delle misurazioni che sono state raccolte cosicché il medico può affidarsi ad uno strumento più evoluto del semplice libretto diario in cui il paziente annota tutte le misurazioni.

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Roos, Sofie. "Chatbots in education : A passing trend or a valuable pedagogical tool?" Thesis, Uppsala universitet, Institutionen för informatik och media, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355054.

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Digitalizing education and reinventing the learning experience is one of the big challenges in this age of information. In the eld of E-learning, the application of a chatbot as part of the education has shown interesting potential, both as a teaching and administrative tool. Chatbots have been 'trending' for a few years and quite a few papers examining it in the educational sector has been published, albeit very little interest seems to have been given to the summation of this knowledge. In an attempt to fill the knowledge gap this thesis performed a literature study to examine the documented features and possible uses for chatbots in an educational context. Since quite a few chatbot technologies have been developed at this time and exhibit varied functions, this study was limited to only examine bots based on the XML derived language AIML. The results imply that chatbots in education have quite a few uses and even more possible features. An AIML-based chatbot can be both simple and complex to implement, all depending on the effort put into implementation. The tool is diverse and may be used for many different purposes and aims, the only limitation being the creators' creativity and imagination.

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Kröger, Felix Jan, and Filip Johansson. "Conversational Commerce : A Quantitative Study on Preferences towards AI-Fueled C-Commerce Platforms among Digital Natives in Sweden and Germany." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-43819.

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Background: E-commerce is widespread in today’s shopping routines and conversational commerce (CC) as an expansion, aims at integrating customers and businesses on a whole new level. Through the application of chatbots fueled by artificial intelligence, a more personal and individual way of remote shopping is offered. Purpose: Our research question What potential attributes of AI-fueled CC applications and their possible inherent characteristics are determining the willingness to use them and to what extent, in the context of digital natives living in Sweden and Germany? aims at identifying the demanded attributes of conversational commerce from a consumer perspective. Method: We facilitate a quantitative questionnaire with 118 valid answers to administer a traditional full-profile conjoint analysis. Conclusion: Our results indicate that German digital natives deem a CC application’s behavior as the most important attribute, followed by payment method, personality and communication form (voice or text). The Swedish digital natives however, attach the most importance to the payment method, followed by behavior, communication form and personality. Both have in common that they prefer a rather passive behavior over being actively approached, a personality that is balanced between humor and seriousness and text-based communication over voice. A difference is the Swedish preference for direct in-app payment while German digital natives would select a redirection to a secondary payment provider (e.g. PayPal).

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Olsen, Linnéa. "Can Chatbot technologies answer work email needs? : A case study on work email needs in an accounting firm." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-85013.

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Work email is one of the organisations most critical tool today. It`s have become a standard way to communicate internally and externally. It can also affect our well-being. Email overload has become a well-known issue for many people. With interviews, follow up interviews, and a workshop, three persons from an accounting firm prioritise pre-define emails needs. And identified several other email needs that were added to the priority list. A thematic analysis and summarizing of a Likert scale was conducted to identify underlying work email needs and work email needs that are not apparent. Three work email needs were selected and using scenario-based methods and the elements of PACT to investigating how the characteristics of a chatbot can help solve the identified work email overload issue? The result shows that email overload is percept different from individual to individual. The choice of how email is handled and email activities indicate how email overload feeling is experienced. The result shows a need to get a sense of the email content quickly, fast collect financial information and information from Swedish authorities, and repetitive, time-consuming tasks. Suggestions on how this problem can be solved have been put forward for many years, and how to use machine learning to help reduce email overload. However, many of these proposed solutions have not yet been implemented on a full scale. One conclusion may be that since email overload is not experienced in the same way, individuals have different needs - One solution does not fit all. With the help of the character of a chatbot, many problems can be solved. And with a technological character of a chatbot that can learn individuals' email patterns, suggest email task to the user and performing tasks to reducing the email overload perception. Using keyword for email intents to get a sense of the email content faster and produce quick links where to find information about the identified subject. And to work preventive give the user remainder and perform repetitive tasks on specific dates.

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Gozzoli, Manuel. "Intelligenza Artificiale: tecniche e applicazioni." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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Hemmingsson, Isak, and Axel Wedebrand. "KAN ARTIFICIELL INTELLIGENS GÖRA OSS EN TJÄNST? : En studie om svenska försäkringsbolags arbete med artificiell intelligens och CRM." Thesis, Umeå universitet, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-174445.

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För många framgångsrika service- och tjänstebolag är Customer RelationshipManagement, eller CRM-system, ett fundamentalt och nödvändigt verktyg som företag brukar för att möjliggöra en förhöjd kundupplevelse och kundnöjdhet för företagetskunder. På senare år har artificiell intelligens genom sin utveckling sett en ökning av potentiella användningsområden och sedermera introducerats inom diverse branscher tack vare dess effektivisering av dessa användningsområden. Men alla branscher har intesett samma implementeringsgrad av olika anledningar. Dels beroende på operationella skillnader, men också på grund av hur kunder ser på användningen av artificiell intelligens som i sin tur påverkat företagens implementering av artificiell intelligens i sina kundrelaterade processer. Med artificiella intelligensens intåg inom den svenska försäkringsbranschen i kombination med de tidigare utförda studier som påpekar problematiken med singulärt fokus på tekniken inom CRM är syftet att undersöka hur svenska försäkringsbolagstrategiskt arbetar med implementering av artificiell intelligens och CRM. Vi har även som förhoppning att skapa en bredare förståelse kring möjligheter och eventuell problematik med artificiell intelligens, CRM och vilka olika mätinstrument som användsför att se om det är en lönsam investering. Baserat på problemdiskussionen kom vi fram till följande frågeställning: Hur arbetar försäkringsbolag i Sverige idag med CRM-system och artificiell intelligensför att skapa kundlojalitet? Den teoretiska referensramen utgörs av sex huvudsakliga teman; Business to Customer,Customer Relationship Management, Artificiell Intelligens, CRM som strategi, Lojalitet och Mätning. Dessa teman sammanfattas sedan med hjälp av en egen syntes inspirerad av Rust & Chungs (2006, s. 562) artikel “Marketing Models of Service and Relationship”. Vi har med en kvalitativ ansats intervjuat sex personer från tre olika försäkringsbolag. Försäkringsbolagen skiljer sig i storlek och har olika syn på både CRM och artificiell intelligens. Vi redogör senare i analysen hur artificiell intelligens och CRM används av försäkringsbolag på den svenska marknaden. I det avseendet ger vi läsare olika exempel på hur artificiell intelligens och CRM kan vara värdeskapande till både företag och kunder. Efter samtliga intervjuer och analys upptäcktes olika gemensamma nämnare hos deundersökta företagen vad gäller både artificiell intelligens och CRM.Implementeringsgraden av artificiell intelligens berodde till stor del på företagensmålkunder, eller mer specifikt på åldern hos målkunderna. Vi identifierade att försäkringsbolagen har arbetat olika länge med både CRM och artificiell intelligens, men är positiva till att båda verktygen kan ge både interna och externa möjligheter. Trots detta skiljer sig användningsgraden av verktygen mellan de undersökta försäkringsbolagen. Ett AI-integrerat CRM-system tillåter nya avenyer att utforskas som tidigare inte varit synonyma med försäkringar och kan således förändra relationen vi har till våra försäkringsbolag.

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Talebi, Roxana, and Julia Timmas. "User Adoption of Cognitive Agents : Identifying success factors from a process perspective." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279631.

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With the rise of intelligent solutions such as cognitive agents, many organizations are trying to identify how they can best utilize the benefits of the technology to make advancements as a company and enhance employee job performance. However, the attempts of many organizations are falling short from their expectations and users do not adopt to the technology. To investigate this problem, a qualitative study was performed with the aim of exploring the different phases of a cognitive agent project process to identify key factors and incentives influencing user adoption, by comparing organizational and individual perspectives. The study results show that 94% of managers see added potential and value in this type of technological initiative, while the number is only 60% for the more operational positions. This indicates a gap between the different perspectives which can hinder successful adoption. The results show that involvement of users throughout the process can decrease this gap. With the increasing complexity of cognitive technology, as it learns over time, the study implies that user awareness and clear expectations through a collaborative process enables increased adoption. Further, the study argues that the adoption process starts earlier than organizations might think. This implies that it is important to look at the life cycle perspective and factors influencing adoption. In order to impact the user adoption rate, this study highlights several factors and incentives, emphasizing on context and the combination of the different aspects, which contribute to higher performance and a wider spread of cognitive agent application.
Med ökningen av intelligenta lösningar, så som kognitiva agenter, gör att många organisationer försöker identifiera hur de kan utnyttja teknikens fördelar bäst för att gynna användarnas effektivitet. Men många organisationers försök lever inte upp till förväntningarna och användarna tar inte till sig tekniken. För att undersöka problemen med detta genomfördes en kvalitativ studie med syftet att utforska de olika faserna i ett kognitiv agent-projekt för att identifiera nyckelfaktorer och incitament som påverkar användandet av lösningen, genom att jämföra det organisatoriska och individuella perspektivet. Studieresultaten visar att 94% av ledarna ser en enorm potential och värde i denna typ av teknikinitiativ, medan endast 60% av de mer operativa användarna upplever värde i en kognitiv agent. Detta indikerar ett gap mellan de olika perspektiven som kan hindra framgångsrik adoption. Resultaten visar att om användare är involverade under hela processen kan det minska detta gap. Med den ökande komplexiteten i kognitiv teknik, som utvecklas över tid, innebär studien att användarmedvetenhet och tydliga förväntningar genom en samarbetsprocess möjliggör ökad adoption. Vidare belyser studien att adoptionsprocessen börjar tidigare än organisationer kan tro. Detta innebär att det är viktigt att titta ur livscykelperspektivet på faktorer som påverkar adoptionen. För att påverka användarnas adoptionsgrad belyser denna studie flera faktorer och incitament, med betoning på kontext och kombinationen av olika aspekter, vilket bidrar till högre prestanda och en bredare spridning av kognitiva agenter.

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Ganrot, William, and Paul Johansson. "Att utveckla en chattbot med Rasa." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-78088.

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Världen blir alltmer digitaliserad och i med det, utvecklas nya metoder för att kunna underlätta arbetet för oss människor med automatiserade system som bland annatkontrolleras av AI (artificiell intelligens). Nya utmaningar står inför dörren för att fåsamhällen att anpassa sig till den nya framtiden. En av dessa metoder är chattbottar sommed hjälp av AI kan automatisera en stor del av det manuella arbetet.Denna uppsats bygger på ett projekt som vi blev tilldelade av CGI, att utvecklaen chattbot som en demoprodukt. Syftet med demoprodukten är att ge CGI möjlighetatt visa för kunder vad en chattbot är för något och vilka användningsområden den kanha. Chattbotten utvecklades med hjälp av ett open source-projekt som kallas för Rasasom är ett ramverk för att utveckla chattbottar med. Resultatet är en demoprodukt i formav en chattbot som kan boka semester och möten samt hjälpa användare att få ett nyttlösenord om de har glömt sitt och svara på vanliga frågor.
The world becomes more and more digital and with that, new methods are being deve-loped to ease the work for us humans with automatic systems including those controlledby AI (Artificial Intelligence). New challenges are faced every day to make us moreaccustomed to the new future. One of the methods is chatbots and with the help of AIthey can be used to automate a big chunk of the manual labour.This dissertation is based on an assignment by CGI, to develop a chatbot as ademo. The purpose of the demo is for CGI to show to customers what a chatbot is andwhat use cases a chatbot can have. The development of the chatbot used an open sourceproject called Rasa which is a framework to create chatbots with. The result is a demo inthe shape of a chatbot that can book vacations and meetings as well as help users receivea new password if they forgot theirs and answer frequently asked questions (FAQ).

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Gustafsson, Rickard, and Oskar Lindfors. "Hello, I'm an AI. What can I help you with? : En explorativ studie som undersöker användares attityder gentemot AI-drivna chatbotar." Thesis, Mittuniversitetet, Institutionen för medie- och kommunikationsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42233.

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Detta är en explorativ studie som undersöker användares attityder gentemot AI-drivna chatbotar. Genom metoden fokusgrupper införskaffade vi empiriskt material som vi kategoriserade och analyserade med hjälp av en tematisk analys. Resultatet visade att användares inställning till chatbotar som kommunikationsverktyg är positiv, men de hade en bestämd uppfattning om vilka typer av uppgifter som lämpar sig för en chatbot och inte.

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Kuylenstierna, Elsa, and Hanna Trägårdh. "Customers perception of Artificial Intelligence as Chatbots in CRM." Thesis, Högskolan i Halmstad, Akademin för företagande, innovation och hållbarhet, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44538.

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ABSTRACT Title: Customers perception of Artificial Intelligence as Chatbots in CRM Subject: Bachelor thesis in business administration, 15 hp Authors: Hanna Trägårdh & Elsa Kuylenstierna Supervisor: Klaus Solberg Söilen Examiner: Ulf Aagerup Keywords: Artificial intelligence, Chatbots, Customer Relationship Management, Generation Z, Generation Y Purpose: The purpose of this study is to determine the perception Swedish customers from Gen Z and Gen Y have of companies using chatbots in customer relationship management. Furthermore the study will analyze if the different generational groups perceive chatbots in different ways. The study also focuses on finding out what role chatbots play in terms of CRM. Methodology: In this study a deductive research approach was used where the empirical study was collected through a survey. The survey had 212 respondents, 100 of them were between 15 and 25 years old and 112 were between 26 and 44 years old. Conclusion: Gen Z and Gen Y have similar opinions about how they perceive chatbots. Both Gen Z and Gen Y prefer communicating with a human since chatbots are not living up to their expectations. However, they are optimistic that chatbots have the potential to improve customer services to the better. Companies need to make sure that chatbots create value for customers and not only for companies themselves. Chatbots need to keep developing and make progress to be beneficial for customers to use. Implications: This study can contribute with new perspectives about chatbots and customer relationships that can be a big advantage for companies when implementing chatbots for their business. The study brings attention to the unexplored issue of Gen Z and Gen Y’s perception in this matter. This study can also be helpful for further research within the subject area.

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Victorin, Karin. "AI as Gatekeepers to the Job Market : A Critical Reading of; Performance, Bias, and Coded Gaze in Recruitment Chatbots." Thesis, Linköpings universitet, Tema Genus, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177257.

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The topic of this thesis is AI recruitment chatbots, digital discrimination, and data feminism (D´Ignazio and F.Klein 2020), where I aim to critically analyze issues of bias in these types of human-machine interaction technologies. Coming from a professional background of theatre, performance art, and drama, I am curious to analyze how using AI and social robots as hiring tools entails a new type of “stage” (actor’s space), with a special emphasis on social acting. Humans are now required to adjust their performance and facial expressions in the search for, and approval of, a new job. I will use my “theatrical glasses” with an intersectional lens, and through a methodology of cultural analysis, reflect on various examples of conversational AI used in recruitment processes. The silver bullet syndrome is a term that points to a tendency to believe in a miraculous new technological tool that will “magically” solve human-related problems in a company or an organization. The captivating marketing message of the Swedish recruitment conversational AI tool – Tengai Unbiased – is the promise of a scientifically proven objective hiring tool, to solve the diversity problem for company management. But is it really free from bias? According to Karen Barad, agency is not an attribute, but the ongoing reconfiguration of the world influenced by what she terms intra-actions, a mutual constitution of entanglement between human and non-human agencies (2003:818). However, tech developers often disregard their entanglement of human-to-machine interferences which unfortunately generates unconscious bias. The thesis raises ethical questions of how algorithmic measurement of social competence risks holding unconscious biases, benefiting those already privileged or those acting within a normative spectrum.

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Kvarnåsen, Josefine. "Hi, I am the new digital co-worker : A qualitative study on employees within the public sector’s expectations and experiences of implementing AI chatbots." Thesis, Högskolan Väst, Avd för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-16876.

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Chatbots are becoming increasingly common within both private and public sectors as they are implemented for organizations to provide service at any time. Within related research on the topic, the focus lies on the private sector and chatbot users, while the research on how chatbot implementation may affect the employees within the public sector is lacking. The focus of this thesis is therefore to provide more information about chatbot implementation within the public sector. More specifically, to understand how the employees expect and experience that the implementation of chatbots can affect them in their work and ways to communicate information. In this study, eight semi-structured interviews with a duration of one hour each were conducted, where the interviewees were employees in municipalities and universities who are working with chatbot implementation. The results show that the interviewees expect that there will be a decreased workload and increased time to work on more complex tasks. However, the time that is liberated because of the chatbot needs to be reinvested into its upkeep, and the interviewees experience that new tasks are added to fill that time, indicating that their expectations are unfulfilled. The results also show that the interviewees expect the chatbot to increase their availability and that it will be a new, less formal way to communicate information. It is experienced that people can contact them any time through the chatbot. They experience that the chatbot uses a simple language to communicate information and that it presents information like it would be presented by a human.

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Ryberg, Daniel. "Chattbotar : Upplevelser, möjligheter och problem inom kundtjänst." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-85051.

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Artificiell intelligens har varit ett omdiskuterat ämne sedan decennier tillbaka och vävs desto mer in i vår vardag allt eftersom tiden går. Vi kan som åskådare bara se på medan vår vardag både kantas, förgylls och radikaliseras av denna teknik som ständigt utvecklas. I denna kvalitativa studie så undersöks det hur chattbotar (även kallade textuella botar) uppfattas av konsumenten inom kundtjänst. Syftet med denna studie är att undersöka konsumenters upplevelsers, möjligheter och problem när det gäller chattbotar inom kundtjänst. Undersökningen bestod av totalt 12 respondenter som medverkade i strukturerade intervjuer. Intervjufrågorna delades in i 4 kategorier (Inledning, användarupplevelser, effektivitet och kundnöjdhet). Kategoriseringarna ämnade att spegla de aspekter som studien indelades i. Resultaten indikerade att en majoritet av respondenterna föredrog att kontakta kundsupport via telefon istället för chattbot. Respondenterna uppgav också att kravet på att precisera sin frågeställning ökade i kontakten med en chattbot. Resultaten påvisade också att den upplevda effektiviteten påverkads av mängden information som uppvisades samt att kundnöjdheten påverkades negativt efter betjänandet av en chattbot. Respondenternas svar visar att fördelar med en chattbot är den konstanta tillgängligheten, den snabba responstiden samt avsaknaden av väntetid. Resultaten indikerar att en dåligt anpassad och chattbot kan bidra till försämrade användarupplevelser bland konsumenter. Emellertid så indikerar även resultaten att den konstanta tillgängligheten hos en chattbot är något som ökar kundnöjdheten. Detta skulle kunna vara en positiv förbättring för ett företag, detta då företagets tillgänglighet ökar och ger konsumenter möjlighet att få sina ärenden besvarade även utanför kontorstid. Studien påvisaratt det är viktigt för företag som funderar på att implementera en chattbot att beakta vilken informationen som visas samt att ha en väl utprovad och genomtänkt struktur på chattboten.

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Toofanee, Mohammud Shaad Ally. "An innovative ecosystem based on deep learning : Contributions for the prevention and prediction of diabetes complications." Electronic Thesis or Diss., Limoges, 2023. https://aurore.unilim.fr/theses/nxfile/default/656b0a1f-2ff2-49c5-bb3e-f34704d6f6b0/blobholder:0/2023LIMO0107.pdf.

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En 2021, le diabète touchait environ 537 millions de personnes dans le monde. Ce chiffre devrait grimper à 643 millions d'ici 2030 et 783 millions d'ici 2045. Le diabète est une maladie métabolique persistante qui nécessite des soins et une gestion quotidiens continus. Le fardeau des maladies chroniques pèse lourdement sur les systèmes de santé lorsqu'il touche une partie substantielle de la population. De telles circonstances ont un impact négatif non seulement sur le bien-être général d'une grande partie de la population, mais contribuent également de manière significative aux dépenses de santé. Dans le contexte de Maurice, selon le rapport le plus récent de la Fédération Internationale du Diabète, la prévalence du diabète, en particulier du diabète de type 2 (T2D), était de 22,6 % de la population en 2021, avec des projections indiquant une hausse à 26,6 % d'ici 2045. Face à cette tendance alarmante, une évolution concomitante a été observée dans le domaine de la technologie, l'intelligence artificielle démontrant des capacités prometteuses dans les domaines de la médecine et de la santé. Cette thèse de doctorat entreprend l'exploration de l'intersection entre l'intelligence artificielle, plus précisément l’apprentissage profond, l'éducation, la prévention, et la gestion du diabète. Nous nous sommes d'abord concentrés sur l'exploration du potentiel de l'Intelligence Artificielle (IA) pour répondre à une complication fréquente du diabète : l'Ulcère du Pied Diabétique (DFU). Les DFU présentent un risque grave d'amputations des membres inférieurs, entraînant des conséquences graves. En réponse, nous avons proposé une solution innovante nommée DFU-HELPER. Cet outil permet de valider les protocoles de traitement administrés par les professionnels de la santé aux patients individuels atteints de DFU. L'évaluation initiale de l'outil a montré des résultats prometteurs, bien qu'un affinement further et des tests rigoureux soient impératifs. Les efforts collaboratifs avec les experts en santé publique seront essentiels pour évaluer l'efficacité pratique de l'outil dans des scénarios réels. Cette approche vise à combler le fossé entre les technologies IA et les interventions cliniques, avec pour objectif ultime d'améliorer la prise en charge des patients atteints de DFU. Notre recherche a également abordé les aspects critiques de la vie privée et de la confidentialité inhérents à la manipulation des données liées à la santé. Reconnaissant l'importance capitale de la protection des informations sensibles, nous avons appliqué une approche avancée d'apprentissage fédéré Peer-to-Peer à notre proposition pour l'outil DFU-Helper. Cette approche permet de traiter des données sensibles sans les transférer vers un serveur central, contribuant ainsi à créer un environnement de confiance et sécurisé pour la gestion des données de santé. Enfin, notre recherche s'est étendue au développement d'un agent conversationnel intelligent conçu pour fournir des informations et un soutien 24 heures sur 24 aux personnes atteintes de diabète. Dans la poursuite de cet objectif, la création d'un jeu de données approprié était essentielle. Dans ce contexte, nous avons utilisé des techniques de traitement du langage naturel pour sélectionner des données de qualité provenant de sources médias en ligne traitant du diabète
In the year 2021, estimations indicated that approximately 537 million individuals were affected by diabetes, a number anticipated to escalate to 643 million by the year 2030 and further to 783 million by 2045. Diabetes, characterized as a persistent metabolic ailment, necessitates unceasing daily care and management. In the context of Mauritius, as per the most recent report by the International Diabetes Federation, the prevalence of diabetes, specifically Type 2 Diabetes (T2D), stood at 22.6% of the population in 2021, with projections indicating a surge to 26.6% by the year 2045. Amidst this alarming trend, a concurrent advancement has been observed in the realm of technology, with artificial intelligence techniques showcasing promising capabilities in the spheres of medicine and healthcare. This doctoral dissertation embarks on the exploration of the intersection between artificial intelligence and diabetes education, prevention, and management.We initially focused on exploring the potential of artificial intelligence (AI), more specifically, deep learning, to address a critical complication linked to diabetes – Diabetic Foot Ulcer (DFU). The emergence of DFU poses the grave risk of lower limb amputations, consequently leading to severe socio-economic repercussions. In response, we put forth an innovative solution named DFU-HELPER. This tool serves as a preliminary measure for validating the treatment protocols administered by healthcare professionals to individual patients afflicted by DFU. The initial assessment of the proposed tool has exhibited promising performance characteristics, although further refinement and rigorous testing are imperative. Collaborative efforts with public health experts will be pivotal in evaluating the practical efficacy of the tool in real-world scenarios. This approach seeks to bridge the gap between AI technologies and clinical interventions, with the ultimate goal of improving the management of patients with DFU.Our research also addressed the critical aspects of privacy and confidentiality inherent in handling health-related data. Acknowledging the extreme importance of safeguarding sensitive information, we delved into the realm of Peer-to-Peer Federated Learning. This investigation specifically found application in our proposal for the DFU-Helper tool discussed earlier. By exploring this advanced approach, we aimed to ensure that the implementation of our technology aligns with privacy standards, thereby fostering a trustworthy and secure environment for healthcare data management.Finally, our research extended to the development of an intelligent conversational agent designed to offer round-the-clock support for individuals seeking information about diabetes. In pursuit of this goal, the creation of an appropriate dataset was paramount. In this context, we leveraged Natural Language Processing techniques to curate data from online media sources focusing on diabetes-related content

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Ljungren, Joakim. "Data-driven design for sustainable behavior : A case study in using data and conversational interfaces to influence corporate settlement." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-139199.

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Interaction with digital products and interfaces concern more and more of human decision-making and the problems regarding environmental, financial and social sustainability are consequences much due to our behavior. The issues and goals of sustainable development therefore implies how we have to think differently about digital design. In this paper, we examine the adequacy of influencing sustainable behavior with a data-driven design approach, applying a conversational user interface. A case study regarding the United Nation’s goals of technological development and economic distribution was conducted, to see if a hypothetical business with a proof-of-concept digital product could be effective in influencing where companies base their operations. The test results showed a lack of usability and influence, but still suggested a potential with language-based interfaces. Even though the results could not prove anything, we argue that leveraging data analysis to design for sustainable behavior could be a very valuable strategy. A data-driven approach could enable ambitions of profit and user experience to coincide with those of sustainability, within a business organization.

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Baptista, Bruno Miguel Costa. "IPBRICK OS - AI Voice/Chatbot." Master's thesis, 2022. https://hdl.handle.net/10216/140739.

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Chen, Chao-An, and 陳昭安. "A Study of Implementing AI Chatbot in Campus Consulting Service." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/zfju86.

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碩士
國立中央大學
資訊工程學系在職專班
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Due to popularize of social networks and instant messaging applications, mobile usage has grown at an unprecedented pace and has become the most efficient way for people to connect. As a result, sparked a new type of service through automated conversational agents, Chatbot. Lowering costs by disseminating information through predesigned processes has become a hot industry research topic. A chatbot is an automated response system through texts or voice messaging, achieved by artificial learning to simulate human communication. This research based on Python for program development utilizes open source web framework Django, Microsoft’s QnA Maker and LUIS for text recognition to design chatbot. Previous chatbot developments require proficient natural language cognition and training through massive language information to reach effective results. This system, however, focuses on minimizing information training time to achieve quicker implementation of in-school information chatbot system; by gathering school’s FAQ pages and threads, automated collection and training will strengthen chatbot’s work processes for effective services. Other than developing chatbot services, this research also suggests managing protocols, including chat logs, inquiring session logs, service quality feedbacks, transference to person and rating feedbacks. Through simplified management and training, visualized monitoring tools, data analysis, backend operator can grasp the effectiveness of interactions in real-time, making sure quality fits its entirety. Most importantly, alleviate servicing staff’s workload, accumulate experience and data, resulting in improvement of the service quality that reaches to 12.63%.

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Schmitt, Charlotte Rosa Maria. "Artificial intelligence in customer service : how chatbots reshape customer service strategies : a guidance for an AI-based chatbot integration." Master's thesis, 2020. http://hdl.handle.net/10400.14/29727.

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The extensive use of e-business interfaces has significantly changed the domain of customer service. Expectations regarding speed, scope and availability of customer service are forcing companies to revise outdated costly and resource intensive customer service strategies. AI-based chatbots, therefore, are gaining significant traction. These virtual assistants promise to serve large numbers of customers individually and efficiently, while being cheaper compared to human agents and scalable. Despite rapid development of the technology, there is limited literature addressing the integration processes of AI-based chatbots. This creates uncertainties for companies endeavoring to implement chatbots. Two research questions animate this thesis: What concrete benefits do chatbots represent for customer service? And how is this technology best integrated to maximize value for companies and customers? Using qualitative and quantitative data collection, this study seeks to determine optimal strategies for chatbot integration. This requires precise understandings of the capabilities and limitations of AI. A company’s customer values, combined with its attitudes towards time-intensive data preparation and agent training, also bear upon strategy optimization. Hybrid human-chatbot models are another iteration shown to generate value. Building upon research, this dissertation proposes strategies for integrating chatbots into existing customer service. The integration process will be divided into four phases and each phase will be evaluated separately with respect to different conditions and obstacles.
A ampla utilização de interfaces de comércio electrónico alterou significativamente o domínio do serviço ao cliente. As expectativas em relação à velocidade, âmbito e disponibilidade do serviço ao cliente estão a forçar as empresas a reverem estratégias de serviço ao cliente dispendiosas e desatualizadas, que exigem muitos recursos. Os chatbots, portanto, estão ganhando tração significativa no atendimento ao cliente. Estes assistentes virtuais prometem servir um grande número de clientes de forma individual e eficiente, sendo baratos e escaláveis. Apesar do rápido desenvolvimento da tecnologia, há pouca literatura sobre os processos de integração de chatbots. Isso promove incertezas para as empresas que se esforçam para implementar chatbots. Questões de pesquisa animam esta tese: Que benefícios concretos os chatbots representam para o serviço ao cliente? E como esta tecnologia é melhor integrada para maximizar o valor para empresas e clientes? Usando a coleta de dados qualitativos e quantitativos, este estudo procura determinar as estratégias ideais para a integração do chatbot. Isso requer entendimentos precisos das capacidades e limitações da IA. Os valores dos clientes de uma empresa, combinados com suas atitudes em relação à preparação de dados com tempo intensivo e treinamento de agentes, também influenciam na otimização da estratégia. Os modelos híbridos de humanos-chatbot são outra iteração demonstrada para gerar valor. Com base em pesquisas, esta dissertação propõe estratégias para a integração de chatbots no serviço ao cliente existente. O processo de integração será dividido em quatro fases e cada fase será avaliada separadamente em relação a diferentes condições e obstáculos.

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Yi-ChengWang and 王逸程. "Human Resource Allocation in an Online Customer Service Chat System with AI-based Chatbot." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/b7zgx8.

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碩士
國立成功大學
工業與資訊管理學系
107
Customer service plays an important role between organizations and its customers. Among different types of customer service, a unique feature of customer service chat (CSC) is that agents can serve multiple customers simultaneously. The intelligent assistant (Chatbot) that emerged along with the development of artificial intelligence has become an auxiliary tool for the CSC system. The organization imports the chatbot to the front interface of its CSC system for reducing the waiting time of customers and improving customer satisfaction. And the introduction of chatbot also affects the human resource allocation of the CSC system inherent in the organization. This study builds a CSC system that introduces a feedback-enabled chatbot through a simulation model and uses the simulation optimization tool to explore the human resource allocation strategy at different customer arrival rates. It also compares the total cost, as well as the percentage of abandonment before and after the import. The results of the simulation experiments revealed that in the case of low customer arrival rate, the introduction of the chatbot did not significantly reduce the average customer cost in the initial stage. In the long term, implementing chatbot brings significantly lower average total customer cost and the percentage of abandonment to the CSC system than the system without chatbots at three different arrival rates.

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Angara, Prashanti Priya. "Towards a deeper understanding of current conversational frameworks through the design and development of a cognitive agent." Thesis, 2018. https://dspace.library.uvic.ca//handle/1828/10374.

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In this exciting era of cognitive computing, conversational agents have a promising utility and are the subject of this thesis. Conversational agents aim to offer an alternative to traditional methods for humans to engage with technology. This can mean to reduce human effort to complete a task using reasoning capabilities and by exploiting context, or allow voice interaction when traditional methods are not available or inconvenient. This thesis explores technologies that power conversational applications such as virtual assistants, chatbots and conversational agents to gain a deeper understanding of the frameworks used to build them. This thesis introduces Foodie, a conversational kitchen assistant built using IBM Watson technology. The aim of Foodie is to assist families in improving their eating habits through recipe recommendations taking into account personal contexts, such as allergies and dietary goals while helping reduce food waste and managing grocery budgets. This thesis discusses Foodie's architecture and derives a design methodology for building conversational agents. This thesis explores context-aware systems and their representation in conversational applications. Through Foodie, we characterize the contextual data and define its methods of interaction with the application. Foodie reasons using IBM Watson's conversational services to recognize users' intents and understand events related to the users and their context. This thesis discusses our experiences in building conversational agents with Watson, including features that may improve the development experience for creating rich conversations.
Graduate

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Díaz, Herrera Juan Camilo. "Conversational AI Assistant Using Artificial Neural Networks: Implementation of a contextual chatbot framework in a Point-of-Sale system." Master's thesis, 2021. http://hdl.handle.net/10362/127803.

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Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
Artificial intelligence is changing the way how businesses are affronting their day-to-day difficulties. Chatbots are the perfect demonstration of how simple tasks and queries such as customer support or sales metrics and reporting could be solved without human intervention. This project introduced a task-oriented chatbot framework for Spanish language in a Point-Of-Sale webpage. We applied Natural Language Processing (NLP) techniques such as NER and evaluated two supervised learning methods: (i) an Artificial Neural Network (ANN) and (ii) a Support Vector Machines (SVM) model to create a contextualized chatbot that classifies the user’s intention in a text conversation, allowing bidirectional human-to-machine communication. These intents could go from simple chitchatting to detailed reports, always providing a natural flow in conversation. The results using an augmented and balanced corpus suggested that ANN model performed statistically better than SVM. Additionally, a real-word scenario with a small-talk survey made to five users gave positive feedback about the quality of predictions. Finally, a software architecture using a PaaS computing service and an API framework was proposed to implement this dialog system in further works.

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CHEN, YING, and 陳穎. "The Influence of Message Direction on Attribute Benefit and Purchase Intention is Applied to the Logical Design of AI Chatbot." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/pr38rx.

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碩士
東海大學
餐旅管理學系
107
This study explores the combinatory effects of attribute benefit and message direction on consumer’s final purchase intention, through the transmission of chatbot. A two-factor experimental design was employed with attribute benefit (hedonic value vs. utilitarian value) and message direction (positive message vs. negative message) as the control variables, and getting the total valid data of 160 from the experimental subjects in Z generation. The results showed that individual analysis of product attributes or message direction on the purchase intention is nonsignificant, however, the combinatory of product benefit and message direction on purchase intention are significant. Besides, the results suggest that the product in hedonic value with positive message should be recommended to process benefit’s consumer, on the other hand, the chatbot has to recommend the product in utilitarian value with negative message to outcome benefit’s consumer. With this combination, the consumer’s purchase intention and the willingness to pay can be generated and increased.In the application, by finding the best way to communicate the message, which can provide the suggestion to the logical design of AI chatbot, and also increase the distance and communication between the vendors and consumers.

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Kaywan, Payam. "Human Depression Analysis: An Experimental Study of the Use of AI Botics for Early Detection." Thesis, 2022. https://vuir.vu.edu.au/43946/.

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The world is facing a shortage of professional medical staff, a situation which has been exacerbated by the COVID-19 pandemic which has significantly increased challenges globally and has had an adverse impact on the health care system. This has also led to additional barriers to patient care access, specifically for individuals who are in need of constant special care. To address the issue of limited access to medical professionals, medical assistance can be provided to patients in the form of a chatbot which acts as a proxy between psychiatrists and patients and is available and accessible 24/7. Although there has been a degree of success in developing medical chatbots, many medical professionals believe that the use of chatbots in early depression detection needs to be more practical which will require further research. In this research, we address the well-known and common shortcomings which have been discussed in the recent literature. Three of these shortcomings are as follows: firstly, there is a lack of open-ended questions to enable participants to interact openly and without any restrictions about their moods and emotions as most bots in the literature constrain the participants’ responses by limiting them to multiple choice questions which means the participants are not able to open up and describe their real feelings freely. Secondly, there is a lack of semantic analysis to draw exact meaning from a text. Thirdly, there is a requirement for participants to make a long-term commitment in terms of their involvement in the research. This research introduces a depression analysis chatbot, DEPRA, which aims to resolve some of these shortcomings and challenges by asking open-ended questions, providing semantic analyses and automatic depression scoring. DEPRA is developed using contemporary bot platforms, Dialogflow on Google cloud-based infrastructure, and is integrated with social network platforms such as Facebook. Most chatbots today are designed for therapeutic purposes. However, the DEPRA chatbot is designed with a focus on the detection of depression in its early stages. DEPRA is designed based on a structured early detection depression Standard Interview Guideline the Hamilton Depression Scale (SIGH-D) and Inventory of Depressive Symptomatology (IDS-C), which is used by professional psychiatrists in triage sessions with patients. DEPRA has been trained with personalized utterances from a focus group. This research utilizes Natural Language Processing (NLP) to identify the depression level of participants based on their recorded conversation. DEPRA uses a scoring system to determine the participant’s depression level and severity. This research also details a non-clinical trial with 50 participants who interacted with the DEPRA chatbot. Due to the ethical limitations of this research, such as only residents of Australia and participants to be in the age group of 18 to 80 years old, we have approached a dataset with only 50 participants. This size of dataset was suitable to conduct and run the research. However, the future studies will target a more comprehensive dataset. This study was a first stage of utilizing Chatbot for early detection of depression. In this stage our goal was to develop the system not to run the clinical trial. Therefore, we required a sample that could assist us mainly to identify the accuracy of the system developed. Future work is to access evaluation by human expert which goes into the next phase of the project and could also include extending the sample and/or enhancing the system further and the assistance would be offered to western health. Therefore, at this stage 50+ sample sufficed to capture various responses by the people that had participants of different level of depression. To evaluate the autoscoring feature of DEPRA, the accuracy of the Machine Learning (ML) algorithms is calculated. Accordingly, manual scoring is compared with the calculated depression scores. The average accuracy of the 27 questions related to the linear SVC of the 26 participants’ experiment is 88%, the SGD algorithm of 40 participants’ experiment is 80%, and the linear SVC of 50 participants’ experiment is 87%. Furthermore, the overall satisfaction rate of using DEPRA was 79% indicating that the participants had a high rate of user satisfaction and engagement.

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Hoppe, Niklas. "Disruptive innovation in the healthcare sector : the advent of AI chatbots." Master's thesis, 2020. http://hdl.handle.net/10400.14/31219.

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Over the last several decades, the healthcare sector has faced many challenges. These include a shortage of doctors, especially in rural areas, high clinical costs, and an increasing number of diseases needing to be treated. This thesis focuses on the potential and the limitations of an innovative way to solve problems in healthcare – use of AI chatbots. We highlight the user’s perspective concerning AI healthcare chatbot technology. Based on qualitative and quantitative research, we conclude that this novel technology offers new opportunities for diagnostics, enables work to be carried out more efficiently, and gives the patient the power to “self-diagnose”. AI chatbots have not yet reached their full potential due to legal restrictions, insufficient data, and the lack of capacity to integrate them into different systems. Even though the number of AI chatbot users is increasing, people trust chatbots less than doctors. To enhance user engagement and create a higher level of trust, credible entities such as doctors and the government could recommend the use of AI chatbots. The general acceptance of chatbots has to be analyzed per country since it is explained by socio-economic factors (education, age, income), personality-related factors (attitude to new things, curiosity) and communication behavior factors.
Nas últimas décadas, o setor da saúde enfrentou muitos desafios. Nestes podem destacar-se a escassez de médicos, especialmente nas zonas rurais, custos de tratamento elevados e um número crescente de doenças a precisarem de ser tratadas. Esta tese foca-se no potencial e nas limitações de uma forma revolucionária de resolver problemas na área da saúde – o uso de chatbots de IA. Destacamos a perspetiva do utilizador em relação à assistência médica através da tecnologia de chatbot de IA. Com base em pesquisas qualitativas e quantitativas, concluímos que esta tecnologia inovadora oferece novas oportunidades para diagnósticos, permite que o trabalho seja realizado com mais eficiência e oferece ao paciente a capacidade de se autodiagnosticar. Os chatbots de IA ainda não atingiram todo o seu potencial devido a restrições legais, dados insuficientes e à falta de capacidade de integrá-los em diferentes sistemas. Ainda que o número de utilizadores de chatbot de IA esteja a aumentar, as pessoas confiam menos nos chatbots do que nos médicos. Para encorajar um maior envolvimento do utilizador e criar um nível mais alto de confiança, entidades credíveis como médicos e o governo podem recomendar o uso de chatbots de IA. A aceitação generalizada dos chatbots deve ser analisada por país, uma vez que é explicada por fatores socioeconómicos (educação, idade, rendimento), fatores relacionados com a personalidade (atitude perante coisas novas, curiosidade) e fatores de comportamento na comunicação.

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Dissertations / Theses on the topic 'AI ChatBot'

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