Academic literature on the topic 'Support Ticket'

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Journal articles on the topic "Support Ticket"

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Maddens, Bart. "Gesplitst stemmen bij de parlementsverkiezingen van 21 mei 1995 : een analyse op basis van surveydata." Res Publica 41, no. 4 (1999): 421–50. http://dx.doi.org/10.21825/rp.v41i4.18490.

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The 1995 simultaneous election of three legislative assemblies (Senate, lower Chamber and regional councils) offered the Belgian voters an opportunity to split their ballot between three different parties. An analysis of Flemish individual level survey data shows that 76.1% cast a straight ticket vote, white 20.9 % split their tickets between two and 3 % between three different parties. Ticketsplitting occurs most frequently amongst voters who mention the personality of individual politicians or the issues as a reason to support a party. In addition, the likehood of ticket-splitting increases
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Bajpai, Himanshu. "Building ML Based Intelligent System to Analyze Production LSI Live Site Incidents." International Journal of Engineering and Advanced Technology 10, no. 3 (2021): 41–46. http://dx.doi.org/10.35940/ijeat.c2178.0210321.

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Providing support on the rolled-out application/services is one of the major factors in increasing the customer satisfaction which in turn increases the customer retention. Since we are in the era of automation where most of the day-to-day jobs are taken care of or are facilitated by the technologies around us, hence there is a need to reduce manual effort in triaging the support tickets and hence facilitating the person on call to better close the tickets on time with proper remediation. The machine learning model which will be the product of this complete paper will not only help in classify
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Makowsky, Michael D., and Thomas Stratmann. "Political Economy at Any Speed: What Determines Traffic Citations?" American Economic Review 99, no. 1 (2009): 509–27. http://dx.doi.org/10.1257/aer.99.1.509.

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Speeding tickets are determined not only by the speed of the offender, but also by incentives faced by police officers and their vote-maximizing principals. We hypothesize that police officers issue fines more frequently when drivers have a higher opportunity cost of contesting a ticket, and when drivers are not residents of the local municipality. We also predict that local officers are more likely to issue a ticket to out-of-town drivers when fiscal conditions are tight and legal limits prevent increases in property taxes. Using data from traffic stops in Massachusetts, we find support for o
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Courty, Pascal. "Some Economics of Ticket Resale." Journal of Economic Perspectives 17, no. 2 (2003): 85–97. http://dx.doi.org/10.1257/089533003765888449.

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A large number of brokers and scalpers resell a significant fraction of event tickets at substantial markups and they manage to do so despite the fact that promoters and ticketing agencies do not support resell for profits and often attempt to block secondary market. Why can't promoters capture the profits from secondary markets or at least deter brokers from doing so? I present a simple explanation that borrows from the literature on airline ticket pricing and draw parallels with that literature. I review some evidence consistent with this explanation.
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Bogojeska, Jasmina, Ioana Giurgiu, George Stark, and Dorothea Wiesmann. "IBM Predictive Analytics Reduces Server Downtime." INFORMS Journal on Applied Analytics 51, no. 1 (2021): 63–75. http://dx.doi.org/10.1287/inte.2020.1064.

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IBM has deployed its Predictive Analytics for Server Incident Reduction (PASIR) solution to more than 360 information technology (IT) environments worldwide since 2013. These environments, covering sectors from banking to travel to e-commerce, are serviced by IBM support groups. Incidents occurring on servers, including problem descriptions and resolutions, are documented in client account-specific ticket management systems. PASIR uses machine learning to classify the incident tickets within an IT environment and identify high-impact incidents that involve server outages by using the respectiv
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C. Regoeczi, Wendy, and Stephanie Kent. "Race, poverty, and the traffic ticket cycle." Policing: An International Journal of Police Strategies & Management 37, no. 1 (2014): 190–205. http://dx.doi.org/10.1108/pijpsm-06-2013-0060.

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Purpose – Through systematic observation of police decision-making behavior, the aim of this paper is to investigate what factors differentiate between citizens who receive a warning vs a ticket from police and whether the influence of those factors varies by race. The paper also explores the context of those decisions for both blacks and whites to further the understanding of the underlying mechanisms of any observed differences in the likelihood of receiving a ticket vs a warning. Design/methodology/approach – Data were collected during police ridealongs conducted in a sample of cities withi
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Montgomery, Lloyd, Daniela Damian, Tyson Bulmer, and Shaikh Quader. "Customer support ticket escalation prediction using feature engineering." Requirements Engineering 23, no. 3 (2018): 333–55. http://dx.doi.org/10.1007/s00766-018-0292-3.

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Beck, Paul Allen, Lawrence Baum, Aage R. Clausen, and Charles E. Smith. "Patterns and Sources of Ticket Splitting in Subpresidential Voting." American Political Science Review 86, no. 4 (1992): 916–28. http://dx.doi.org/10.2307/1964344.

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The primary source of divided government in the United States is voters who split their ballots between the parties. Yet there has been little comprehensive examination of either patterns or sources of ticket splitting in recent years. Instead, divergent lines of research have emerged, emphasizing such things as voter partisanship, incumbency, and a “new” (young, well-educated, even partisan) kind of ticket splitter; and their focus has been too often restricted to the atypical president–Congress pair. We seek to unify these research traditions in a comprehensive model of split-ticket voting a
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Zou, Tianxin, and Baojun Jiang. "Integration of Primary and Resale Platforms." Journal of Marketing Research 57, no. 4 (2020): 659–76. http://dx.doi.org/10.1177/0022243720917352.

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Consumers can buy concert tickets from primary platforms (e.g., Ticketmaster) or from consumer-to-consumer resale platforms (e.g., StubHub). Recently, Ticketmaster has entered and been trying to control the resale market by prohibiting consumers from reselling on competing resale platforms. Several states in the United States have passed or are discussing laws requiring tickets to be transferrable on any resale sites, worrying that platform integration—Ticketmaster controlling both the primary and the resale platforms—will increase ticket service fees and harm musicians and consumers. This art
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Powell, Michael, Jamison A. Rotz, and Kevin D. O’Malley. "How Machine Learning Is Improving U.S. Navy Customer Support." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 08 (2020): 13188–95. http://dx.doi.org/10.1609/aaai.v34i08.7023.

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The U.S. Navy is successfully using natural language processing (NLP) and common machine-learning (ML) algorithms to categorize and automatically route plain text support requests at a Navy fleet support center. The algorithms enhance routine IT support tasks with automation and reduce the workload of service desk agents. The ML pipeline works in a five-step process. First, an archive of documents is created from various sources, including standard operating procedure (SOP) memos, frequently asked questions (FAQs), knowledge articles, Wikipedia articles, encyclopedia articles, previously close
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Dissertations / Theses on the topic "Support Ticket"

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Fiati-Kumasenu, Albert. "Extracting Customer Sentiments from Email Support Tickets : A case for email support ticket prioritisation." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18853.

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Background Daily, companies generate enormous amounts of customer support tickets which are grouped and placed in specialised queues, based on some characteristics, from where they are resolved by the customer support personnel (CSP) on a first-in-first-out basis. Given that these tickets require different levels of urgency, a logical next step to improving the effectiveness of the CSPs is to prioritise the tickets based on business policies. Among the several heuristics that can be used in prioritising tickets is sentiment polarity. Objectives This study investigates how machine learning meth
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Middents, Janelle. "UNDERSTANDING THE SPLIT-TICKET VOTER." Master's thesis, University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3958.

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This thesis will focus on split ticket voting. Split ticket voting refers to an aspect of voting behavior where the individual will cast votes for different political parties for different offices. Through the development of countless theories and utilizing data, political scientists have managed to shed some light as to why an individual may engage in split-ticket voting. However, many of these studies have been too narrow in their focus, for instance, relying on a specific election without taking into account some major variables that provide the foundation for voting behavior. The purpose o
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Andersson, Martin, and Marcus Mazouch. "Binary classification for predicting propensity to buy flight tickets. : A study on whether binary classification can be used to predict Scandinavian Airlines customers’ propensity to buy a flight ticket within the next seven days." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855.

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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it’s simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics
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Valério, Rafael Mendonça. "Projecto de data mining e modelação preditiva na TAP Portugal : relatório de estágio." Master's thesis, Instituto Superior de Economia e Gestão, 2014. http://hdl.handle.net/10400.5/8342.

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Mestrado em Gestão de Sistemas de Informação<br>Este relatório de estágio dá a conhecer a importância que as ferramentas de análise preditiva como o data mining e a modelação preditiva têm para o sistema de Business Intelligence de uma organização. No caso concreto, tem-se como objeto de trabalho o sistema de gestão de receitas de uma companhia aérea portuguesa que nele identificou uma oportunidade de otimização. O projeto realizado teve como foco a implementação de uma componente de data mining que permitisse antecipar a receita relativa a bilhetes comprados mas não utilizados, geradora de
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Laurentz, Henrik. "Feasibility of using network support data to predict risk level of trouble tickets." Thesis, Linköpings universitet, Programvara och system, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-128656.

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Internet Service Providers gather vast amounts of data in the form of trouble tickets created from connectivity related issues. This data is often stored and seldom used for proactive purposes. This thesis explores the feasibility of finding correlations in network support data through the use of data mining activities. Correlations such as these could be used for improving troubleshooting or staffing related activities. The approach uses the data mining methodology CRISP-DM to investigate typical data mining operations from the perspective of a Network Operation Center. The results show that
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Moharreri, Kayhan. "Augmenting Collective Expert Networks to Improve Service Level Compliance." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500649086849134.

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Larsson, Andreas. "Development of a customer support process tool in SharePoint Online." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119221.

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Management thinking has changed focus from bringing in new customers to under- standing the significance of maintaining existing customers and the need to attain loyalty with these customers. This has increased the importance of keeping good customer relationships. One important element to attain good customer relations is through a solid customer support. In this thesis a customer support approach for a software consultancy company has been implemented. The goal was to create a SharePoint Online application that would work as a single point of contact for the customers to improve the issue re
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Magona, Joseph Webeleta. "Point of care diagnosis of bovine trypanosomosis, tick-borne diseases and helminthoses with emphasis on portable anaemia-detection devices and decision support systems." Thesis, University of Glasgow, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407706.

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De, moura braga Elayne. "Enseignement apprentissage de la statistique, TICE et environnement numérique de travail : étude des effets de supports didactiques numériques, médiateurs dans la conceptualisation en statistique." Thesis, Lyon 2, 2009. http://www.theses.fr/2009LYO20021/document.

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Définissant les Technologies de l’Information et de la Communication dans l’Education (TICE) comme médiateurs dans l’apprentissage, nous réalisons une recherche sur le support didactique numérique « Méthodes Quantitatives FORSE », disponible aux étudiants de Licence en Sciences de l’Education Formation à Distance (CNED) afin de proposer des compléments pour que les TICE deviennent des bons médiateurs. La formation à distance à travers les TICE exige une nouvelle lecture de l’éducation, des pratiques et des rôles des sujets impliqués (apprenant, contenu, support, éducateur). Nous montrons quels
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Leclet, Dominique. "Environnements Interactifs d'Apprentissage dans des contextes professionnels : Des Tuteurs Intelligents aux Systèmes Supports d'Apprentissage à Distance." Habilitation à diriger des recherches, Université de Picardie Jules Verne, 2004. http://tel.archives-ouvertes.fr/edutice-00001474.

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Nous présentons dans cette HDR nos activités de recherche depuis une dizaine d'années, qui se déclinent sous la forme de méthodes, de systèmes prototypés et expérimentés, en milieu écologique présentiel ou distanciel, et ce dans des contextes professionnels variés. Ces activités de recherche se déclinent, également, sous la forme d'actions sur le terrain permettant d'émettre de nouvelles hypothèses de recherche. Comme le souligne le titre de l'HDR « Environnements Interactifs d'Apprentissage dans des contextes professionnels : des Tuteurs Intelligents aux Systèmes Supports d'Apprentissage à Di
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Books on the topic "Support Ticket"

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Clare, Beswick, and Hardy Martha, eds. Tickle and tumble: Feeling safe and supported. Featherstone Education, 2003.

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World, Anne Smith. Composition Notebook: Just Put in a Ticket Computer Science IT Support Funny Gift, Journal 6 X 9, 100 Page Blank Lined Paperback Journal/Notebook. Independently Published, 2020.

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Preston, Katherine K. The American Opera Company. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199371655.003.0007.

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This chapter focuses on the philanthropist Jeannette Thurber, who founded the American (National) Opera Company (1885) to encourage high-caliber performances of continental operas translated into English. Her company was heavily subsidized by New York society and supported by establishment music critics. But both Thurber and her musical director Theodore Thomas misunderstood the American opera audience, and mounted serious works designed for cultural uplift, to the neglect of Italian and French operas that were popular among the general public. Society members were not interested in English-la
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O’Connell, Sue. Lyme borreliosis. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198570028.003.0009.

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Lyme borreliosis is the most common vector-borne bacterial infection in the temperate northern hemisphere. In the United States of America over 35,000 confirmed or probable cases were reported by state health departments to the Centers for Disease Control and Prevention (CDC) in 2008. It is likely that well over 100,000 cases occur in Europe each year. Lyme borreliosis is caused by several genospecies of Borrelia burgdorferi sensu lato, which are transmitted by ticks of the Ixodes ricinus complex. The infection occurs most commonly in forested, woodland and heathland habitats that support the
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Grand Opera House (London, Ont.), ed. Grand Opera House, London, Ont.: Saturday, September 17th, '92, programme : the popular and versatile actress Josie Mills, supported by her excellent new company and fine brass band and grand operatic orchestra ... Ticket of leave man .. s.n., 1986.

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Krause, Andreas, and Volker Fingerle. Lyme borreliosis. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0101.

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Lyme borreliosis (LB) is a multisystem infectious disease caused by the tick-borne spirochete Borrelia burgdorferi. The most frequent clinical manifestations include erythema migrans, meningoplyneuritis, and arthritis. Diagnosis of LB is made on clinical grounds and usually supported by a positive serology. Early diagnosis and treatment almost always leads to a rapid healing of the disease. However, in late manifestations gradual remission of symptoms may take several weeks to months. In rare cases, the pathogen can persist for many years or induce a persisting immunopathological response that
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Krause, Andreas, and Volker Fingerle. Lyme borreliosis. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199642489.003.0101_update_001.

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Lyme borreliosis (LB) is a multisystem infectious disease caused by the tick-borne spirochete Borrelia burgdorferi. The most frequent clinical manifestations include erythema migrans, meningoplyneuritis, and arthritis. Diagnosis of LB is made on clinical grounds and usually supported by a positive serology. Early diagnosis and treatment almost always leads to a rapid healing of the disease. However, in late manifestations gradual remission of symptoms may take several weeks to months. In rare cases, the pathogen can persist for many years or induce a persisting immunopathological response that
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Book chapters on the topic "Support Ticket"

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Curtis, Daniel. "Support Ticket Application." In Practical Oracle JET. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4346-6_3.

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Mour, Vishal, Sreya Dey, Shipra Jain, and Rahul Lodhe. "Feature Store for Enhanced Explainability in Support Ticket Classification." In Natural Language Processing and Chinese Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60457-8_38.

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Trivedi, Suyog, Balaji Jagan, and Gopichand Agnihotram. "A Multilingual Framework for a Question Answering System for the Support of Ticket Data: An Extended Approach." In Natural Computing for Unsupervised Learning. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98566-4_6.

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Az, Şevval, Uygar Takazoğlu, and Aşkın Karakaş. "Text Classification Models for CRM Support Tickets." In Trends in Data Engineering Methods for Intelligent Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79357-9_8.

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Wu, Yao, Jian Cao, Yudong Tan, and Quanwu Xiao. "A Data-Driven Agent-Based Simulator for Air Ticket Sales." In Computer Supported Cooperative Work and Social Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1377-0_16.

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Léonard, Luc, Guy Leduc, and André Danthine. "The Tick-Tock Case Study for the Assessment of Timed FDTs." In The OSI95 Transport Service with Multimedia Support. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85165-0_20.

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Nagy, Gabor I., and Krisztian Buza. "SOHAC: Efficient Storage of Tick Data That Supports Search and Analysis." In Advances in Data Mining. Applications and Theoretical Aspects. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31488-9_4.

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Chikhaoui, Ons, Aida Ben Chehida, Ryma Abassi, and Sihem Guemara El Fatmi. "A Formal Ticket-Based Authentication Scheme for VANETs." In Artificial Intelligence and Security Challenges in Emerging Networks. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7353-1.ch008.

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Vehicular ad hoc networks (VANETs) enable vehicles to exchange safety-related messages in order to raise drivers' awareness about surrounding traffic and roads conditions. Nevertheless, since these messages have a crucial effect on people's lives and as we cannot disregard the probability of attackers intending to subvert the proper operation of these networks, stringent security support should be applied on these messages before they can be relied on. Authenticating these messages before considering them is one of the key security requirements since it enables the receiver to make sure of the received message's integrity and the genuineness of its originator. This chapter presents a conditional privacy-preserving authentication scheme for VANETs.
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Lynch, John Roy. "1881: Republican and Greenback Alliance." In Reminiscences of an Active Life, edited by John Hope Franklin. University Press of Mississippi, 2008. http://dx.doi.org/10.14325/mississippi/9781604731149.003.0028.

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This chapter highlights the 1881 election in Mississippi for governor and other state officers. What was known as the Greenback, or Populist, party had made some headway in the state, especially in the Second, or Holly Springs, Congressional District. It looked at that time as if that party would cut an important figure in the politics of the state. Believing that the Greenback party was strong enough to secure a fair election and an honest count in localities where it had an organized existence, it was suggested that the Republicans and Greenbackers form a fusion, the two parties to unite in the support of one state ticket. The suggestion was favorably received. However, it occurred to John Roy Lynch that the ticket would be very much stronger if they could find a liberal and conservative Democrat who would be willing to accept the nomination for governor. The man he had in mind at the time was State Senator Benjamin King of Copiah County.
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Billheimer, John. "Hitchcock and Selznick." In Hitchcock and the Censors. University Press of Kentucky, 2019. http://dx.doi.org/10.5810/kentucky/9780813177427.003.0006.

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This chapter describes the interactions between Hitchcock and David O. Selznick when the director came to America to work for Selznick International. The two men were a mismatched pair, Selznick flamboyant and Hitchcock withdrawn, but they were united in their love of movies. Hitchcock resented Selznick’s memo-writing interference and welcomed his loan-outs to other studios, but Selznick gave the director his ticket to America and the financial support and star access he needed to make first-rate films. Subsequent chapters examine the impacts of censorship on each of the ten films Hitchcock made while under contract to Selznick.
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Conference papers on the topic "Support Ticket"

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Montgomery, Lloyd, Emma Reading, and Daniela Damian. "ECrits — Visualizing Support Ticket Escalation Risk." In 2017 IEEE 25th International Requirements Engineering Conference (RE). IEEE, 2017. http://dx.doi.org/10.1109/re.2017.62.

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Santana, Everton, Saulo Mastelini, and Sylvio Jr. "Deep Regressor Stacking for Air Ticket Prices Prediction." In XIII Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação, 2017. http://dx.doi.org/10.5753/sbsi.2017.6022.

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Purchasing air tickets by the lowest price is a challenging task for consumers since the prices might fluctuate over time influenced by several factors. In order to support users’ decision, some price prediction techniques have been developed. Considering that this problem could be solved by multi-target approaches from Machine Learning, this work proposes a novel method looking forward to obtaining an improvement in air ticket prices prediction. The method, called Deep Regressor Stacking (DRS), applies a naive deep learning methodology to reach more accurate predictions. To evaluate the contr
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Chen, I.-Chang, Shu-Keng Hsu, Teh-Juan Wu, et al. "RDSP: A Railway Decision Support Platform for Integrating and Bridging Existed Legacy Systems." In 2013 Joint Rail Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/jrc2013-2442.

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Railway system operation is a very complicated task and must be supported by the coordination of several systems including engineering, transportation, locomotive maintenance and management, ticket system and passengers service, etc. Ideally, a modern railway enterprise information system should be an integrated, consisted, and site-opened database to support railway system operation. However, multiple isolated applications instead of one integrated enterprise information system are often formed due to historical factors such as independent departments, budgetary constraint and application req
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Xu, Yuchang, and Jian Cao. "OTPS: A decision support service for optimal airfare Ticket Purchase." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258068.

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Gajananan, Kugamoorthy, Pablo Loyola, Yasuharu Katsuno, Asim Munawar, Scott Trent, and Fumiko Satoh. "Modeling Sentiment Polarity in Support Ticket Data for Predicting Cloud Service Subscription Renewal." In 2018 IEEE International Conference on Services Computing (SCC). IEEE, 2018. http://dx.doi.org/10.1109/scc.2018.00014.

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Zicari, Paolo, Gianluigi Folino, Massimo Guarascio, and Luigi Pontieri. "Discovering accurate deep learning based predictive models for automatic customer support ticket classification." In SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing. ACM, 2021. http://dx.doi.org/10.1145/3412841.3442109.

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Montgomery, Lloyd, and Daniela Damian. "What do Support Analysts Know About Their Customers? On the Study and Prediction of Support Ticket Escalations in Large Software Organizations." In 2017 IEEE 25th International Requirements Engineering Conference (RE). IEEE, 2017. http://dx.doi.org/10.1109/re.2017.61.

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Liao, Hao-yu, Willie Cade, and Sara Behdad. "Forecasting Repair and Maintenance Services of Medical Devices Using Support Vector Machine." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-63966.

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Abstract Accurate prediction of product failures and the need for repair services become critical for various reasons, including understanding the warranty performance of manufacturers, defining cost-efficient repair strategies, and compliance with safety standards. The purpose of this study is to use machine learning tools to analyze several parameters crucial for achieving a robust repair service system, including the number of repairs, the time of the next repair ticket or product failure, and the time to repair. A large dataset of over 530,000 repairs and maintenance of medical devices has
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Cordera Piñera, Rubén, Roberto Sañudo, Luigi Dell'Olio, and Ángel Ibeas. "Demand prediction model for regional railway services considering spatial effects between stations." In CIT2016. Congreso de Ingeniería del Transporte. Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.4053.

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The railways are a priority transport mode for the European Union given their safety record and environmental sustainability. Therefore it is important to have quantitative models available which allow passenger demand for rail travel to be simulated for planning purposes and to evaluate different policies. The aim of this article is to specify and estimate trip distribution models between railway stations by considering the most influential demand variables. Two types of models were estimated: Poisson regression and gravity. The input data were the ticket sales on a regional line in Cantabria
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Blaz, Cássio Castaldi Araujo, and Karin Becker. "Sentiment analysis in tickets for IT support." In ICSE '16: 38th International Conference on Software Engineering. ACM, 2016. http://dx.doi.org/10.1145/2901739.2901781.

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