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Dissertations / Theses on the topic 'RECOMMENDATION TECHNIQUES'

Author: Grafiati

Published: 11 September 2023

Last updated: 26 July 2025

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1

Martins, Diogo Marques. "Trajectory clustering techniques with application to route recommendation." Master's thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/18581.

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Mestrado em Engenharia de Computadores e Telemática<br>O uso generalizado de dispositivos capazes de obter e transmitir dados sobre a localização de objetos ao longo do tempo tem permitido recolher grandes volumes de dados espácio-temporais. Por isso, tem-se assistido a uma procura crescente de técnicas e ferramentas para a análise de grandes volumes de dados espácio-temporais com o intuito de disponibilizar uma gama variada de serviços baseados na localização. Esta dissertação centra-se no desenvolvimento de um sistema para recomendaSr trajetos com base em dados históricos sobre a localizaçã

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Vahabi, Hossein. "Recommendation techniques for Web search and social media." Thesis, IMT Alti Studi Lucca, 2012. http://e-theses.imtlucca.it/86/1/Vahabi_phdthesis.pdf.

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Recommenders aim to solve the information and interaction overload. A recommender system is a tool that identifies highly relevant items of interest for a user. In this thesis we aim to harness the information available through Web to build recommender systems. In particularwe study on a number of different recommendation problems: "correct tag recommendation", "query recommendation", "tweet recommendation", and "tourist points of interest recommendation". For each problem, we describe and evaluate effective solutions using novel efficient techniques.

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Alabdulrahman, Rabaa. "Towards Personalized Recommendation Systems: Domain-Driven Machine Learning Techniques and Frameworks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41012.

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Recommendation systems have been widely utilized in e-commerce settings to aid users through their shopping experiences. The principal advantage of these systems is their ability to narrow down the purchase options in addition to marketing items to customers. However, a number of challenges remain, notably those related to obtaining a clearer understanding of users, their profiles, and their preferences in terms of purchased items. Specifically, recommender systems based on collaborative filtering recommend items that have been rated by other users with preferences similar to those of the targ

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Aleksandra, Klašnja-Milićević. "Personalized Recommendation Based on Collaborative Tagging Techniques for an e‐Learning System." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2013. https://www.cris.uns.ac.rs/record.jsf?recordId=83535&source=NDLTD&language=en.

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The  research  topic  involves  personalization  of  an  e‐learning  system  based  oncollaborative  tagging  techniques  integrated  in  a  recommender  system.  Collaborative  tagging systems allow users to upload their resources, and to label them with arbitrary words, so‐called tags.  The  systems  can  be  distinguished  according  to  what  kind  of  resources  are  supported. Besides helping user to organize his or her personal c

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Nagi, Mohamad. "Integrating Network Analysis and Data Mining Techniques into Effective Framework for Web Mining and Recommendation. A Framework for Web Mining and Recommendation." Thesis, University of Bradford, 2015. http://hdl.handle.net/10454/14200.

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The main motivation for the study described in this dissertation is to benefit from the development in technology and the huge amount of available data which can be easily captured, stored and maintained electronically. We concentrate on Web usage (i.e., log) mining and Web structure mining. Analysing Web log data will reveal valuable feedback reflecting how effective the current structure of a web site is and to help the owner of a web site in understanding the behaviour of the web site visitors. We developed a framework that integrates statistical analysis, frequent pattern mining, clusterin

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Guerrini, Gabriele. "Analysis, design and implementation of a parking recommendation system applying machine learning techniques." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23162/.

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Nowadays, smart city and urban mobility topics are focusing growing interest for business and R\&D purposes both, and one of its trendy application regards the study and the realization of parking recommendation systems. In our case, a parking recommendation system is going to be developed for the city of Bologna. After a brief revision of similar proposed solutions and their approaches and findings, a first data analysis phase is going to be executed to explore the data and to mine any useful information about the parking behavior. Then, once the adopted forecasting model has been exposed,

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Cabir, Hassane Natu Hassane. "A Comparison Of Different Recommendation Techniques For A Hybrid Mobile Game Recommender System." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615173/index.pdf.

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As information continues to grow at a very fast pace, our ability to access this information effectively does not, and we are often realize how harder is getting to locate an object quickly and easily. The so-called personalization technology is one of the best solutions to this information overload problem: by automatically learning the user profile, personalized information services have the potential to offer users a more proactive and intelligent form of information access that is designed to assist us in finding interesting objects. Recommender systems, which have emerged as a solution to

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Videla, Cavieres Iván Fernando. "Improvement of recommendation system for a wholesale store chain using advanced data mining techniques." Tesis, Universidad de Chile, 2015. http://repositorio.uchile.cl/handle/2250/133522.

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Magíster en Gestión de Operaciones<br>Ingeniero Civil Industrial<br>En las empresas de Retail, las áreas de Customer Intelligence tienen muchas oportunidades de mejorar sus decisiones estratégicas a partir de la información que podrían obtener de los registros de interacciones con sus clientes. Sin embargo se ha convertido en un desafío poder procesar estos grandes volúmenes de datos. Uno de los problemas que se enfrentan día a día es segmentar o agrupar clientes. La mayoría de las empresas generan agrupaciones según nivel de gasto, no por similitud en sus canastas de compra, como propone la

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Holländer, John. "Investigating the performance of matrix factorization techniques applied on purchase data for recommendation purposes." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20624.

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Automated systems for producing product recommendations to users is a relatively new area within the field of machine learning. Matrix factorization techniques have been studied to a large extent on data consisting of explicit feedback such as ratings, but to a lesser extent on implicit feedback data consisting of for example purchases.The aim of this study is to investigate how well matrix factorization techniques perform compared to other techniques when used for producing recommendations based on purchase data. We conducted experiments on data from an online bookstore as well as an onlin

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Bambia, Meriam. "Jointly integrating current context and social influence for improving recommendation." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30110/document.

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La diversité des contenus recommandation et la variation des contextes des utilisateurs rendent la prédiction en temps réel des préférences des utilisateurs de plus en plus difficile mettre en place. Toutefois, la plupart des approches existantes n'utilisent que le temps et l'emplacement actuels séparément et ignorent d'autres informations contextuelles sur lesquelles dépendent incontestablement les préférences des utilisateurs (par exemple, la météo, l'occasion). En outre, ils ne parviennent pas considérer conjointement ces informations contextuelles avec les interactions sociales entre les u

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Goetz, Charity. "Textile dyes techniques and their effects on the environment with a recommendation for dyers concerning the Green effect /." Lynchburg, Va. : Liberty University, 2008. http://digitalcommons.liberty.edu.

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Costa, Arthur Fortes da. "Recomendação de conteúdo baseada em interações multimodais." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-09042015-153225/.

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A oferta de produtos,informação e serviços a partir de perfis de usuários tem tornado os sistemas de recomendação cada vez mais presentes na Web, aumentando a facilidade de escolha e de permanência dos usuários nestes sistemas. Entretanto, existem otimizações a serem feitas principalmente com relação à modelagem do perfil do usuário. Geralmente, suas preferências são modeladas de modo superficial, devido à escassez das informações coletadas,como notas ou comentários, ou devido a informações indutivas que estão suscetíveis a erros. Esta dissertação propõe uma ferramenta de recomendação ba

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Embarak, Ossama Hashem Khamis. "A new technique for intelligent web personal recommendation." Thesis, Heriot-Watt University, 2011. http://hdl.handle.net/10399/2503.

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Personal recommendation systems nowadays are very important in web applications because of the available huge volume of information on the World Wide Web, and the necessity to save users’ time, and provide appropriate desired information, knowledge, items, etc. The most popular recommendation systems are collaborative filtering systems, which suffer from certain problems such as cold-start, privacy, user identification, and scalability. In this thesis, we suggest a new method to solve the cold start problem taking into consideration the privacy issue. The method is shown to perform very well i

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Ammari, Ahmad N. "Transforming user data into user value by novel mining techniques for extraction of web content, structure and usage patterns. The Development and Evaluation of New Web Mining Methods that enhance Information Retrieval and improve the Understanding of User¿s Web Behavior in Websites and Social Blogs." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/5269.

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The rapid growth of the World Wide Web in the last decade makes it the largest publicly accessible data source in the world, which has become one of the most significant and influential information revolution of modern times. The influence of the Web has impacted almost every aspect of humans' life, activities and fields, causing paradigm shifts and transformational changes in business, governance, and education. Moreover, the rapid evolution of Web 2.0 and the Social Web in the past few years, such as social blogs and friendship networking sites, has dramatically transformed the Web from a ra

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Ammari, Ahmad N. "Transforming user data into user value by novel mining techniques for extraction of web content, structure and usage patterns : the development and evaluation of new Web mining methods that enhance information retrieval and improve the understanding of users' Web behavior in websites and social blogs." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/5269.

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The rapid growth of the World Wide Web in the last decade makes it the largest publicly accessible data source in the world, which has become one of the most significant and influential information revolution of modern times. The influence of the Web has impacted almost every aspect of humans' life, activities and fields, causing paradigm shifts and transformational changes in business, governance, and education. Moreover, the rapid evolution of Web 2.0 and the Social Web in the past few years, such as social blogs and friendship networking sites, has dramatically transformed the Web from a ra

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Wu, Kevin (Kevin L. ). "DeepTuner : a system for search technique recommendation in program autotuning." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/115462.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September 2015.<br>"July 2015." Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 86-89).<br>OpenTuner can help users achieve better or more portable performance in their specific domain through program autotuning. A key challenge for users seeking good autotuning performance in OpenTuner is selecting a search approach appropriate for problem. However, not only are current in-situ learning search approaches not robust enough to handle all search s

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Zou, Hai Tao. "Local topology of social networks in supporting recommendations and diversity identification of reviews." Thesis, University of Macau, 2015. http://umaclib3.umac.mo/record=b3335434.

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Almuhaimeed, Abdullah. "Enhancing recommendations in specialist search through semantic-based techniques and multiple resources." Thesis, University of Essex, 2016. http://repository.essex.ac.uk/17584/.

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Information resources abound on the Internet, but mining these resources is a non-trivial task. Such abundance has raised the need to enhance services provided to users, such as recommendations. The purpose of this work is to explore how better recommendations can be provided to specialists in specific domains such as bioinformatics by introducing semantic techniques that reason through different resources and using specialist search techniques. Such techniques exploit semantic relations and hidden associations that occur as a result of the information overlapping among various concepts in mul

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Rammal, Dina. "Thermo-mechanical behaviour of geothermal structures : numerical modelling and recommendations." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10172/document.

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Les structures géothermiques agissent comme éléments échangeurs de chaleur en plus de leur rôle majeur en tant que structures porteuses. De ce fait, ils sont soumis à des sollicitations thermiques en plus des charges mécaniques. Cependant, leurs méthodes de dimensionnement ne sont pas encore clairement définies. Ce travail est divisé en deux parties principales qui couvrent le dimensionnement thermique et mécanique des pieux géothermiques et des parois moulées. En ce qui concerne les performances thermiques des structures géothermiques, deux stratégies sont introduites qui sont capables d'éval

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Armstrong, Norma B. "Software estimating : a description and analysis of current methodologies with recommendations on appropriate techniques for estimating RIT Research Corporatin software projects /." Online version of thesis, 1987. http://hdl.handle.net/1850/10296.

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ALCANTARA, MARCELA C. "Avaliacao dos criterios de qualidade de imagem e estudo das doses em um departamento de mamografia." reponame:Repositório Institucional do IPEN, 2009. http://repositorio.ipen.br:8080/xmlui/handle/123456789/9470.

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Made available in DSpace on 2014-10-09T12:27:06Z (GMT). No. of bitstreams: 0<br>Made available in DSpace on 2014-10-09T13:56:46Z (GMT). No. of bitstreams: 0<br>Dissertacao (Mestrado)<br>IPEN/D<br>Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

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Mkpong, Offiong Etim. "The effects of variable moisture levels on extractable Bray-l P, Bray-l Al, Bray-l Fe, Bray-l Mn : fertilizer P recommendation based on quicktest technique /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487329662144707.

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Zomahoun, Damien Esse. "Emergsem : une approche d'annotation collaborative et de recherche d'images basée sur les sémantiques émergentes." Thesis, Dijon, 2015. http://www.theses.fr/2015DIJOS019/document.

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L’extraction de la sémantique d’une image est un processus qui nécessite une analyse profonde du contenu de l’image. Elle se réfère à leur interprétation à partir d’un point de vuehumain. Dans ce dernier cas, la sémantique d’une image pourrait être générique (par exemple un véhicule) ou spécifique (par exemple une bicyclette). Elle consiste à extraire une sémantique simple ou multiple de l’image afin de faciliter sa récupération. Ces objectifs indiquent clairement que l’extraction de la sémantique n’est pas un nouveau domaine de recherche. Cette thèse traite d’une approche d’annotation collabo

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Lima, Alexandre da Silva. "Form filling recommendation using machine learning techniques." Master's thesis, 2019. https://hdl.handle.net/10216/119419.

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Chen, Yu-Hsuan, and 陳宇軒. "QA Document Recommendation Techniques for Knowledge Communities." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/56260803619245722369.

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博士<br>國立交通大學<br>資訊管理研究所<br>102<br>With the emergence of Social Media, Social Question-Answering (SQA) websites have become common knowledge production and sharing platforms. This platform provides knowledge community services where users with common interests, needs or expertise can form a knowledge community. Community members can collect and share QA knowledge (documents) regarding their interests. However, due to the massive amount of QAs created every day, information overload can become a major problem. Consequently, a recommender system is needed to suggest QA documents for communities o

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Xu, Guandong. "Web mining techniques for recommendation and personalization." Thesis, 2008. https://vuir.vu.edu.au/1422/.

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Nowadays Web users are facing the problems of information overload and drowning due to the significant and rapid growth in the amount of information and the number of users. As a result, how to provide Web users with more exactly needed information is becoming a critical issue in web-based information retrieval and Web applications. In this work, we aim to address improving the performance of Web information retrieval and Web presentation through developing and employing Web data mining paradigms. Web data mining is a process that discovers the intrinsic relationships among Web data, which are

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Xu, Guandong. "Web mining techniques for recommendation and personalization." 2008. http://eprints.vu.edu.au/1422/1/xu.pdf.

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Nowadays Web users are facing the problems of information overload and drowning due to the significant and rapid growth in the amount of information and the number of users. As a result, how to provide Web users with more exactly needed information is becoming a critical issue in web-based information retrieval and Web applications. In this work, we aim to address improving the performance of Web information retrieval and Web presentation through developing and employing Web data mining paradigms. Web data mining is a process that discovers the intrinsic relationships among Web data, which are

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Guo, X. "Personalized government online services with recommendation techniques." Thesis, 2006. http://hdl.handle.net/10453/37083.

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University of Technology, Sydney. Faculty of Information Technology.<br>With the integration of information from different government agencies, a vast resource of information and services may be gathered in one portal. Many businesses have difficulty locating the required information and services. In such a situation of vast information overload, one of the difficulties facing governments is how to provide businesses with information specific to their needs, rather than an undifferentiated mass of information. One way to do this is through the development of personalized government online serv

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LEE, YEU TUNG, and 李雨瞳. "Personalized Video Recommendation by Using Data Mining Techniques." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/92127895633566878321.

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碩士<br>大葉大學<br>工業工程與科技管理學系碩士在職專班<br>95<br>Due to film piracy and digital television, the visual-audio rental industrial are in keen competitions. Nowadays, most of studies focus on images and customer satisfaction of visual-audio rental store, and only a few studies discuss customer preferences and consumer behavior. The purpose of this study is to realize the association between the customer preferences and the consumer rental behavior, by means of improving profits of visual-audio rental industrial. In this study, we collect data (customers’ personal informations and their consuming records)

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Chen, Hung-Chen, and 陳宏鎮. "Techniques of Music Analysis, Recommendation, and Retrieval for Music Services." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/48586024338205626628.

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博士<br>國立清華大學<br>資訊工程學系<br>96<br>With the growth of Internet, a large amount of music data is available for many music-related applications. It is almost impractical for these applications to satisfy the user requirements manually. To provide efficient services within these applications, the techniques developed for automatic music analysis, recommendation, and retrieval are urgently necessary. In this paper, we consider the applications of interactive music tutorials and distance education at music school. In the two applications, we need to integrate several techniques to achieve the educatio

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Ja-HwungSu and 蘇家輝. "Multimedia Data Mining Techniques for Semantic Annotation, Retrieval and Recommendation." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/05323447331505634288.

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博士<br>國立成功大學<br>資訊工程學系碩博士班<br>98<br>In recent years, the advance of digital capturing technologies lead to the rapid growth of multimedia data in various formats, such as image, music, video and so on. Moreover, the modern telecommunication systems make multimedia data widespread and extremely large. Hence, how to conceptualize, retrieve and recommend the multimedia data from such massive multimedia data resources has been becoming an attractive and challenging issue over the past few years. To deal with this issue, the primary aim of this dissertation is to develop effective multimedia data m

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Chen, JIN-WEI, and 陳勁瑋. "Preference Analysis and Articles Recommendation based on Text Mining Techniques." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/yk8b2n.

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碩士<br>國立雲林科技大學<br>資訊管理系<br>106<br>IN THE INFORMATION AGE, THERE ARE VARIOUS TYPES OF NEW ARTICLES POSTED ON THE INTERNET EVERY DAY. THE NUMBER OF ARTICLES GROWS AT A RAPID SPEED SO THAT READERS HARDLY KEEP TRACK OF THE ARTICLES THEY MIGHT BE INTERESTED. IN THIS PAPER, WE PROPOSED AN APPROACH TO IDENTIFY READERS’ PREFERENCE AND THEN RECOMMEND NEW COMING ARTICLES ACCORDINGLY. SPECIFICALLY, WE USE INFORMATION RETRIEVAL TECHNIQUES TO CALCULATE TF-IDF OF WORDS IN THE ARTICLES, SELECT REPRESENTATIVE WORDS AS KEYWORDS, AND THEN BUILD A KEYWORDS DICTIONARY. READER’S PREFERENCE IS CONSTRUCTED AS A KEYW

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陳銘憲. "On Query Recommendation Techniques for the Criminal Case Knowledge Base." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/fr66p3.

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碩士<br>中央警察大學<br>資訊管理研究所<br>106<br>In order to enhance the effectiveness of criminal investigation, the Criminal Investigation Bureau of the National Police Agency under the Ministry of the Interior has built a Criminal Case Knowledge Base to meet the needs and characteristics of criminal investigators. The Criminal Case Knowledge Base collects relevant data on suspects, such as their identification card numbers, names, license plate numbers, offenses charged and case numbers. So far, the Criminal Case Knowledge Base has become one of the most important tools for supporting and assisting crimin

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Yeh, Hsin-Ho, and 葉信和. "Intelligent Music Recommendation Techniques by Mining Context Information and Musical Contents." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/24420779600126900281.

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碩士<br>國立成功大學<br>資訊工程學系碩博士班<br>97<br>Advanced networking and telecommunication technologies make the ease of mobile information retrieval. However, it is hard for the users to find what she/he prefers under large music databases and variant context conditions. To solve this problem, some previous music recommenders have been proposed for providing preferable music automatically. Unfortunately, current music recommenders only based on user’s rating log cannot earn the user’s satisfaction in finding the preferred music due to the lacked consideration of context information and sufficient rating d

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Li, Pei-shan, and 李佩珊. "The Recommendation of Elective Courses Using Data Mining and Collaborative Filtering Techniques." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/98121240770913385308.

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碩士<br>雲林科技大學<br>資訊管理系碩士班<br>96<br>In the field of education, students play the role of customer. How to actively offer information and assist them in choosing suitable elective courses are agonizing problems in many universities. Although various recommender systems have been proposed to solve these problems, many studies focus on the arrangement of the learning path between different chapters in the same course, such as e-learning, but only few studies for recommending different courses are proposed. In this study, we proposed a methodology to provide personalized recommendations on elective

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Li, Kun-Hung, and 李坤宏. "An Evaluation Study of Applying Data Mining Techniques in Developing Personalized Recommendation." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/58534521164950627360.

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碩士<br>國立中央大學<br>企業管理研究所<br>91<br>It is recognized that customer relationship management (CRM) is the key point to benefit business, and the first task is to segment customers for providing customized products and services. However, the ways of market segmentation are of variety, and how to design the proper way to separate customers is more significant relatively. Also, recommender systems are used to suggest products to their customers and to provide consumers with information to help them purchase. If the recommendation is specifically designed for individuals, it will be more suitable an

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Bo-WenWang and 王博文. "Data Pre-Processing and Data Mining Techniques for Video Retrieval and Recommendation." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/24023618016292954357.

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BHARDWAJ, ASHISH. "COMPARISON OF VARIOUS RECOMMENDATION TECHNIQUES EMPLOYING LOCATION BASED SERVICES FOR E-COMMERCE WEBSITE." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19478.

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As data has grown tremendously over the last few decades, the management of data also follows its footsteps and created the ocean of opportunities for researchers to come up with best data management techniques. One aspect of data management that is widely used now-a-days is in the E-Commerce industry to showcase the relevant items to the users and predict which items the user will be most interested in. This hurdle Race allows the data scientist/Machine learning Engineers/Data Engineers and even Geo Data Scientist to give the user the best experience once he visits the website for

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Huang, Jerry, and 黃俊榮. "Using Clustering Techniques to Discover the Recommendation Services of Borrowing Books for Libraries." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/83041893230825617362.

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碩士<br>南台科技大學<br>資訊管理系<br>94<br>The fast development in economy of cause in recent years, the collected books amount of the library is increasing fast too, find the books which accord with reader's demand in these a large amount of collected books, it is more and more difficult. So, how can offer the information of the collected books according to reader's need, have already become an important subject of the library at present. On the other hand, the library hopes to offer more information and service to readers too, hope that the collection in the library can try one's best to be utilized eff

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Mota, Maria Dulce Fernandes. "A model for teaching-learning techniques recommendation to support teaching-learning activities design." Doctoral thesis, 2018. https://repositorio-aberto.up.pt/handle/10216/113819.

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Mota, Maria Dulce Fernandes. "A model for teaching-learning techniques recommendation to support teaching-learning activities design." Tese, 2018. https://repositorio-aberto.up.pt/handle/10216/113819.

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Tu, Yi-Ning, and 杜逸寧. "Integrating CBR and Clustering techniques in Collaborative Classification-An application of journal papers recommendation system." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/59064634372046793848.

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碩士<br>國立彰化師範大學<br>資訊管理學系所<br>93<br>This paper tries to apply the clustering approach and collaborative recommendation for using the present experience to make the new users in indexing or searching papers fast and correctly. Besides the user’s experience is very important for the recommendation system, because the past cases could help the new user more quickly to index the paper. We suggest the CBR(Case-Based Reasoning) method for the system remaining the past indexed cases to help new user to index the paper based on the cases which had grouped by the past uses straightly. This research a

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Kolbert, András Péter. "A scalable recommender system : using latent topics and alternating least squares techniques." Master's thesis, 2018. http://hdl.handle.net/10362/34383.

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Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>A recommender system is one of the major techniques that handles information overload problem of Information Retrieval. Improves access and proactively recommends relevant information to each user, based on preferences and objectives. During the implementation and planning phases, designers have to cope with several issues and challenges that need proper attention. This thesis aims to show the issues and challenges in developing high-quality recommender systems. A paper

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Wu, Tzer-Min, and 吳澤民. "A study of applying data mining techniques to maintenance knowledge recommendation -Aircraft maintenance database as example." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/75862413932268429462.

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碩士<br>中原大學<br>資訊管理研究所<br>90<br>Due to the development of information techniques in recent years. Lots of companies have setup information systems to collect the daily operation data and stored these data in the database. In order to enforce the competitive advantage for company. They want to retrieve some useful information and knowledge from data. The maintenance engineering arises from professional field and experience accumulated. Since the development of information techniques, we use information systems to store the knowledge and experience of people in the database. If we can’t transf

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Hsu, Pei-Ying, and 許珮瑩. "A Novel Explainable Mutual Fund Recommendation System Based on Deep Learning Techniques with Knowledge Graph Embeddings." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/wur49w.

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碩士<br>國立交通大學<br>資訊管理研究所<br>107<br>Since deep learning based models have gained success in various fields during recent years, many recommendation systems also start to take advantage of the deep learning techniques. However, while the deep learning based recommendation systems have achieved high recommendation performance, the lack of interpretability may reduce users' trust and satisfaction, while limiting the model to wide adoption in the real world. As a result, to strike a balance between high accuracy and interpretability, or even obtain both of them at the same time, has become a popular

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Tseng, Hsin Hui, and 曾馨慧. "Applying Data Mining Techniques and Hopfield Neural Network to Recommendation Application（Take Waste Application System as the Example）." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/65293837250677845795.

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碩士<br>中華大學<br>資訊管理學系<br>92<br>In recent years,development of the World Wide Web made fast progress.Information unit in enterprises take development of the Web as the main target. Due to the advantages of Web,IT of departments of various software companies have transfered their application systems to be operated in web interface. The main goal is to achieve an interface that can be operated with simple steps. That is,operations with complex steps should be avoided as much as passible. The main goal of this research is to achieve an application system that can be operated with simple

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Chiu, Yung-Hsiang, and 邱永祥. "The Study of Applying Neural Network and Data Mining Techniques to Course Recommendation Base on E-learning Environment." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/82886359874632835710.

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碩士<br>朝陽科技大學<br>資訊管理系碩士班<br>91<br>As for the various applications of Internet, E-learning changes the traditional learning style and elaborates the characteristics of Internet, such as speed, convenience, the ignorance of distance, the enhancement of teaching quality, and the reduced cost. There are many studies has been done regarding E-learning, however, these studies focus more on system unstruction and in curriculeum organization. These does not help the E-learner to select potential courses according to his or her interest. It is, therefore, the goal of this research to propose a better r

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Cheng, Yu-Ling, and 鄭玉玲. "Apply Data Mining Techniques to Implement Personalized Retrieval and Recommendation on Digital Library － the Library of NHU for example." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/07289752881735063109.

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碩士<br>南華大學<br>資訊管理學研究所<br>91<br>Due to the rapid advance of computer-related technology, the large quantities of electronic data produced everyday has been explored and analyzed to discover meaningful information so as to enhance the service quality of digital library. The objective of this study is to enable personalized retrieval and recommendation services on digital library. We utilize the well-defined “New Classification Scheme For Chinese Libraries” to support audience to retrieve the books that they really want. Besides, memory-based reasoning was applied to assign the unlabeled user to

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Li, Tzu-Chi, and 黎子頎. "A Case Study of Using Data Mining Techniques in Service Satisfaction and Customer Recommendation - Use Brand’s Health Museum as An Example." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/htnm5j.

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碩士<br>國立彰化師範大學<br>企業管理學系<br>101<br>This study used the 2011 internal customers’ questionnaires from Brand’s Health Museum, and used IBM SPSS Modeler 15.0 for analyses by considering seven satisfaction items as input variables and customer recommendation as a target variable. First , we used classification and regression tree (CART) to classify and predict the customers’ behaviors. Second, dimension reduction and feature selection were individually performed to identify the variables, and these variables become the input variables for CART. Third, Bayesian network (BN) was applied to repeat the

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Indriana, Marcelli, and 麥瑟莉. "Applying Data Mining Techniques for Tourist Spot Recommendations." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/44860577782092342084.

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碩士<br>中國文化大學<br>資訊管理學系<br>102<br>Recommender systems have become an important research area in past few years. They have been developed for a variety of domains, especially e-commerce. Recommender systems also can be applied in tourism industry to help tourists organizing their travel plans. Recommender systems can be developed by a variety of different techniques such as Content-Based filtering (CB), Collaborative Filtering (CF), and Demographic Filtering (DF). However, each method has its own advantages and disadvantages. For this reason, many previous researches used several mixed methods w

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