Relevant bibliographies by topics / Hybrid Recommendation / Dissertations / Theses
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Dissertations / Theses on the topic 'Hybrid Recommendation'

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Published: 4 June 2021
Last updated: 26 July 2025

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1

Alsalama, Ahmed. "A Hybrid Recommendation System Based on Association Rules." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1250.

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Recommendation systems are widely used in e-commerce applications. Theengine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose a hybrid framework recommendation system to be applied on two dimensional spaces (User × Item) with a large number of users and a small
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Akermi, Imen. "A hybrid model for context-aware proactive recommendation." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30101/document.

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L'accès aux informations pertinentes, adaptées aux besoins et au profil de l'utilisateur est un enjeu majeur dans le cadre actuel caractérisé par une prolifération massive des ressources d'information hétérogènes. Le développement d'appareils mobiles équipés de plusieurs fonctionnalités telles que la caméra, le WIFI, la géo-localisation et bien plus d'autres permettent aux systèmes mobiles de recommandation actuels d'être hautement contextualisés et pouvant fournir à l'utilisateur des informations pertinentes au bon moment quand il en a le plus besoin, sans attendre qu'il établisse une interac
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Strand, Anton, and Markus Gunnarsson. "Code Reviewer Recommendation : A Context-Aware Hybrid Approach." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18288.

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Background. Code reviewing is a commonly used practice in software development. It refers to the process of reviewing new code changes, commonly before they aremerged with the code base. However, in order to perform the review, developers need to be assigned to that task. The problems with a manual assignment includes a time-consuming selection process; limited pool of known candidates; risk of high reuse of the same reviewers (high workload). Objectives. This thesis aims to attempt to address the above issues with a recommendation system. The idea is to receive feedback from experienced devel
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COSTA, ANDREW DINIZ DA. "A HYBRID DIAGNOSTIC-RECOMMENDATION APPROACH FOR MULTI-AGENT SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13383@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Sistemas multi-agentes são sociedades com agentes autônomos e heterogêneos que podem trabalhar em conjunto para alcançar objetivos similares ou totalmente diferentes. Quando falhas acontecem enquanto algum agente de software tenta alcançar seus objetivos, torna-se importante entender porque tais falhas acontecem e o que pode ser feito para remediar tais problemas. Considerando o ambiente distribuído, dinâmico e a natureza dos sistemas multi-agentes, é importante definir os requisitos necessários para realizar diagnósticos
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Yoshii, Kazuyoshi. "Studies on hybrid music recommendation using timbral and rhythmic features." 京都大学 (Kyoto University), 2008. http://hdl.handle.net/2433/136003.

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Ozturk, Gizem. "A Hybrid Veideo Recommendation System Based On A Graph Based Algorithm." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612624/index.pdf.

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This thesis proposes the design, development and evaluation of a hybrid video recommendation system. The proposed hybrid video recommendation system is based on a graph algorithm called Adsorption. Adsorption is a collaborative filtering algorithm in which relations between users are used to make recommendations. Adsorption is used to generate the base recommendation list. In order to overcome the problems that occur in pure collaborative system, content based filtering is injected. Content based filtering uses the idea of suggesting similar items that matches user preferences. In order to use
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Oktay, Fulya. "A Hybrid Recommendation System Capturing The Effect Of Time And Demographic Data." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/2/12612019/index.pdf.

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The information that World Wide Web (WWW) provides have grown up very rapidly in recent years, which resulted in new approaches for people to reach the information they need. Although web pages and search engines are indeed strong enough for us to reach what we want, it is not an efficient solution to present data and wait people to reach it. Some more creative and beneficial methods had to be developed for decreasing the time to reach the information and increase the quality of the information. Recommendation systems are one of the ways for achieving this purpose. The idea is to design a syst
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Mourao, Fernando Henrique de Jesus. "A hybrid recommendation method that combines forgotten items and non-content attributes." Universidade Federal de Minas Gerais, 2014. http://hdl.handle.net/1843/ESBF-9TELK3.

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Recommender Systems (RSs) play important role in many Web applications nowadays, helping users to find their favorite items amid a huge number of options. Among numerous open challenges inherent to RSs, this dissertation addressed the challenge of enhancing the discovery of potentially relevant items for each user. In this sense, we exploited two algorithmic limitations unaddressed in the literature. First, RSs fail to bring back items consumed long ago that are potentially relevant for users nowadays. Second, RSs fail to capture the whole extent on which implicit signals of preferences observ
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9

Lokesh, Ashwini. "A Comparative Study of Recommendation Systems." TopSCHOLAR®, 2019. https://digitalcommons.wku.edu/theses/3166.

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Recommendation Systems or Recommender Systems have become widely popular due to surge of information at present time and consumer centric environment. Researchers have looked into a wide range of recommendation systems leveraging a wide range of algorithms. This study investigates three popular recommendation systems in existence, Collaborative Filtering, Content-Based Filtering, and Hybrid recommendation system. The famous MovieLens dataset was utilized for the purpose of this study. The evaluation looked into both quantitative and qualitative aspects of the recommendation systems. We found t
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Ceylan, Ugur. "An Ontology-based Hybrid Recommendation System Using Semantic Similarity Measure And Feature Weighting." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613754/index.pdf.

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The task of the recommendation systems is to recommend items that are relevant to the preferences of users. Two main approaches in recommendation systems are collaborative filtering and content-based filtering. Collaborative filtering systems have some major problems such as sparsity, scalability, new item and new user problems. In this thesis, a hybrid recommendation system that is based on content-boosted collaborative filtering approach is proposed in order to overcome sparsity and new item problems of collaborative filtering. The content-based part of the proposed approach exploits semanti
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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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Kaufman, Jaime C. "A Hybrid Approach to Music Recommendation: Exploiting Collaborative Music Tags and Acoustic Features." UNF Digital Commons, 2014. http://digitalcommons.unf.edu/etd/540.

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Recommendation systems make it easier for an individual to navigate through large datasets by recommending information relevant to the user. Companies such as Facebook, LinkedIn, Twitter, Netflix, Amazon, Pandora, and others utilize these types of systems in order to increase revenue by providing personalized recommendations. Recommendation systems generally use one of the two techniques: collaborative filtering (i.e., collective intelligence) and content-based filtering. Systems using collaborative filtering recommend items based on a community of users, their preferences, and their browsing
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Wiklund, Ida. "A Recommendation system for News Push Notifications- Personalizing with a User-based and Content-based Recommendation system." Thesis, Umeå universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172275.

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The news landscape has changed during recent years because of the digitization. News can nowadays be found in both newspapers and on different sites online. The availability of the digital newspapers leads to competition among the news companies. To make the users stay on one specific platform for news, relevance is required in the content and oneway of creating relevance is through personalization, to tailor the content to each user. The focus of this thesis is therefore personalizing newspush notifications for a digital  newspaper and making them more relevant for users. The project was made
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Nyberg, Selma. "Video Recommendation Based on Object Detection." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-351122.

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In this thesis, various machine learning domains have been combined in order to build a video recommender system that is based on object detection. The work combines two extensively studied research fields, recommender systems and computer vision, that also are rapidly growing and popular techniques on commercial markets. To investigate the performance of the approach, three different content-based recommender systems have been implemented at Spotify, which are based on the following video features: object detections, titles and descriptions, and user preferences. These systems have then been 
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Bunnell, Lawrence. "FinPathlight: Framework for an Ontology-Based, Multiagent, Hybrid Recommender System Designed to Increase Consumer Financial Capability." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5801.

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This study is a design science research (DSR) project in which a description of the development and evaluation process for several novel technological artifacts will be communicated. Specifically, this study will establish: 1) an ontology of recommender systems issues, 2) an ontology of financial capability goals, and 3) a framework for a Personal Financial Recommender System (PFRS) application designed to improve user financial capability, called FinPathlight. The impetus for the RecSys Issues Ontology is to address a gap in the literature by providing researchers with a comprehensive knowled
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Pequeno, Paulo Andrà Lima. "A Recommendation system with hybrid content filtering for virtual learning environments as a tool for supporting students and monitoring numerous classes." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12894.

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The provision of educational sources on the Web through specific portals or by public libraries has given democratic spaces to both students and teachers to support their educational routine. However, it is always a challenge to make all that diversity of resources useful to each individual having into consideration their needs. This dissertation seeks to contribute providing students and teachers with a computational environment to help in the learning process. This solution connected to a Learning Virtual Environment and an Exercise Virtual Environment allows students to have an automatic tu
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Pagnossim, José Luiz Maturana. "Uma abordagem híbrida para sistemas de recomendação de notícias." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-07062018-101232/.

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Sistemas de Recomendação (SR) são softwares capazes de sugerir itens aos usuários com base no histórico de interações de usuários ou por meio de métricas de similaridade que podem ser comparadas por item, usuário ou ambos. Existem diferentes tipos de SR e dentre os que despertam maior interesse deste trabalho estão: SR baseados em conteúdo; SR baseados em conhecimento; e SR baseado em filtro colaborativo. Alcançar resultados adequados às expectativas dos usuários não é uma meta simples devido à subjetividade inerente ao comportamento humano, para isso, SR precisam de soluções eficientes e efic
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Lundström, Fredrik, and Sofia Sandberg. "Effektiviteten av rekommendationssystems olika filtreringstekniker: En strukturerad litteraturstudie." Thesis, Uppsala universitet, Informationssystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-354068.

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Mängden data som transporteras över Internet idag är stor. Vilket innebär att det finns ett överflöd av information och ett behov för att urskilja relevant innehåll mot irrelevant. För att uppnå detta används rekommendationssystem som i sin tur använder olika filtreringstekniker. Det finns tre huvudtyper av tekniker, innehållsbaserad kollaborativ filtrering och hybrid tekniker. Syftet med studien är att jämföra olika filtreringstekniker och undersöka hur teknikerna förhåller sig till träffsäkerhet mot testset, beräkningsbelasning och användarnöjdhet. För att genomföra
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Gkatzioura, Anna. "A hybrid approach for item collection recommendations : an application to automatic playlist continuation." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/664040.

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Current recommender systems aim mainly to generate accurate item recommendations, without properly evaluating the multiple dimensions of the recommendation problem. However, in many domains, like in music, where items are rarely consumed in isolation, users would rather need a set of items, designed to work well together, while having some cognitive properties as a whole, related to their perception of quality and satisfaction. In this thesis, a hybrid case-based recommendation approach for item collections is proposed. In particular, an application to automatic playlist continuation, address
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Akarohid, Yuwadee. "Overview of IEC Recommendations for renewable energy and hybrid systems for rural electrification." Thesis, Akarohid, Yuwadee (2017) Overview of IEC Recommendations for renewable energy and hybrid systems for rural electrification. Honours thesis, Murdoch University, 2017. https://researchrepository.murdoch.edu.au/id/eprint/38682/.

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The International Electrotechnical Commission (IEC) is a universal company having a major mission to arrange International standards. IEC TS 62257 introduced herein is one of those series. It concerns about rural electrification which is further away from the national main power line. It is very expensive to get a few single users to utilise a grid to meet cost-effective. Therefore the stand-alone electrical systems are taken into account to serve better situations. In these days, rural electrification is played one of the important strategies to maximise comfort to those people in rural area
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Ben, Ticha Sonia. "Recommandation personnalisée hybride." Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0168/document.

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Face à la surabondance des ressources et de l'information sur le net, l'accès aux ressources pertinentes devient une tâche fastidieuse pour les usagers de la toile. Les systèmes de recommandation personnalisée comptent parmi les principales solutions qui assistent l'utilisateur en filtrant les ressources, pour ne lui proposer que celles susceptibles de l’intéresser. L’approche basée sur l’observation du comportement de l’utilisateur à partir de ses interactions avec le e-services est appelée analyse des usages. Le filtrage collaboratif et le filtrage basé sur le contenu sont les principales te
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Ben, Ticha Sonia. "Recommandation personnalisée hybride." Electronic Thesis or Diss., Université de Lorraine, 2015. http://www.theses.fr/2015LORR0168.

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Face à la surabondance des ressources et de l'information sur le net, l'accès aux ressources pertinentes devient une tâche fastidieuse pour les usagers de la toile. Les systèmes de recommandation personnalisée comptent parmi les principales solutions qui assistent l'utilisateur en filtrant les ressources, pour ne lui proposer que celles susceptibles de l’intéresser. L’approche basée sur l’observation du comportement de l’utilisateur à partir de ses interactions avec le e-services est appelée analyse des usages. Le filtrage collaboratif et le filtrage basé sur le contenu sont les principales te
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Andersson, Morgan. "Personal news video recommendations based on implicit feedback : An evaluation of different recommender systems with sparse data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-234137.

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The amount of video content online will nearly triple in quantity by 2021 compared to 2016. The implementation of sophisticated filters is of paramount importance to manage this information flow. The research question of this thesis asks to what extent it is possible to generate personal recommendations, based on the data that news videos implies. The objective is to evaluate how different recommender systems compare to complete random, each other and how they are received by users in a test environment. This study was performed during the spring of 2018, and explore four different algorithms.
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Tan, Heng Chuan. "Vers des communications de confiance et sécurisées dans un environnement véhiculaire." Thesis, Paris, ENST, 2017. http://www.theses.fr/2017ENST0063/document.

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Le routage et la gestion des clés sont les plus grands défis dans les réseaux de véhicules. Un comportement de routage inapproprié peut affecter l’efficacité des communications et affecter la livraison des applications liées à la sécurité. D’autre part, la gestion des clés, en particulier en raison de l’utilisation de la gestion des certificats PKI, peut entraîner une latence élevée, ce qui peut ne pas convenir à de nombreuses applications critiques. Pour cette raison, nous proposons deux modèles de confiance pour aider le protocole de routage à sélectionner un chemin de bout en bout sécurisé
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Tan, Heng Chuan. "Vers des communications de confiance et sécurisées dans un environnement véhiculaire." Electronic Thesis or Diss., Paris, ENST, 2017. http://www.theses.fr/2017ENST0063.

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Le routage et la gestion des clés sont les plus grands défis dans les réseaux de véhicules. Un comportement de routage inapproprié peut affecter l’efficacité des communications et affecter la livraison des applications liées à la sécurité. D’autre part, la gestion des clés, en particulier en raison de l’utilisation de la gestion des certificats PKI, peut entraîner une latence élevée, ce qui peut ne pas convenir à de nombreuses applications critiques. Pour cette raison, nous proposons deux modèles de confiance pour aider le protocole de routage à sélectionner un chemin de bout en bout sécurisé
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Almeida, Fábio André da Cunha. "Hybrid approach to content recommendation." Master's thesis, 2012. http://hdl.handle.net/10216/67427.

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Almeida, Fábio André da Cunha. "Hybrid approach to content recommendation." Dissertação, 2012. http://hdl.handle.net/10216/67427.

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Weng, Yu-Cheng, and 翁毓成. "Construction of Library Book Recommendation System Based on Hybrid Recommendation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/nng82m.

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碩士<br>南臺科技大學<br>資訊管理系<br>106<br>The recommendation system plays a very important role in the field of e-commerce. It can help users find the desired product more easily, so as to increase the consumer's desire for consumption, and can be used to target the trading behavior and preferences of past customers. Achieving adaptive services will increase sales. 　　The system will adopt the following (1) Content-Based (2) Collaborative Filtering (3) Reader Popular Borrow Recommendation List (4) The Expert Recommend List has four functions that link the books associated with each other for the purpose
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Lipczak, Marek. "Hybrid Tag Recommendation in Collaborative Tagging Systems." 2012. http://hdl.handle.net/10222/14735.

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The simplicity and flexibility of tagging allows users to collaboratively create large, loosely structured repositories of Web resources. One of its main drawbacks is the need for manual formulation of tags for each posted resource. This task can be eased by a tag recommendation system, the objective of which is to propose a set of tags for a given resource, user pair. Tag recommendation is an interesting and well-defined practical problem. Its main features are constant interaction with users and availability of large amounts of tagged data. Given the opportunities (e.g., rich user feedback)
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Pestana, Ana Silva. "Collaborative-demographic hybrid for financial: product recommendation." Master's thesis, 2021. http://hdl.handle.net/10362/113081.

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Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>Due to the increased availability of mature data mining and analysis technologies supporting CRM processes, several financial institutions are striving to leverage customer data and integrate insights regarding customer behaviour, needs, and preferences into their marketing approach. As decision support systems assisting marketing and commercial efforts, Recommender Systems applied to the financial domain have been gaining increased attention. This thesis studies
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Guo, Ding-Wei, and 郭丁瑋. "A Study of Hybrid Music Recommendation Systems." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/60375934526068526914.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>104<br>Recently, recommender system (RS) is a popular topic in academic arena for researchers. There are recommender systems for music, movie, book and so on. In this paper, we propose a method that combines the classical user-based collaborative filtering method and the item-based collaborative filtering method. We then employ the hetrec2011-lastfm-2k dataset from Last.fm, the social music website, to test the proposed music recommender system. Experiment results show that the proposed method outperforms the classical methods (user-based and item-based). Moreover, w
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Cheng, Yi-Shan, and 鄭伊珊. "A Modified Hybrid Recommendation Mechanism using clustering concept." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/dm7u39.

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碩士<br>中原大學<br>資訊管理研究所<br>98<br>In the era of information explosion, a lot of information surrounds our daily life. It is important that helping people to filter out unnecessary data can improve their performance on obtaining appropriate information. Therefore, this study adopts some user profile information to construct user preference model. This research also develops a classified method and a simulated tool to recommend items and contents for users. Firstly, the proposed method uses k-means clustering method to group users according to their personal attributes. Secondly, we use neural netw
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Matos, Paulo Sérgio dos Santos. "Hybrid recommendation system for young athletes training advice." Doctoral thesis, 2020. http://hdl.handle.net/10348/10703.

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Tese submetida à Universidade de Trás-os-Montes e Alto Douro, para obtenção do grau de Doutor em Informática<br>Information and Communication Technologies (ICTs) are being increasingly used in sports, especially in professional football teams, to enhance athletes’ preparation and improve their performances and team results. Professional football clubs use a wide range of commercial software applications and electronic equipment, to collect and process their players’ data. However, these classes of equipment and programs are not accessible to young athletes, as the cost of this software and equ
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Yeh, Shu-Wei, and 葉書瑋. "A Hybrid Recommendation System for SCORM-Compliant Courses." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/62490493165681855755.

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碩士<br>淡江大學<br>資訊工程學系資訊網路與通訊碩士班<br>96<br>With the development of internet technology, interactive distance learning is becoming a new trend of E-learning. In the future, we believe that there will be a large number of digital SCORM-compliant courses in repository for the user. Consequently, when a learner confronts a large amount of learning materials, it is hard to select appropriate and preferred courses to learn. This thesis proposed a hybrid recommendation system for SCORM-compliant courses. By using three proposed recommendation modules, it can raise the accuracy of searching course and in
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Chen, Yu-Chih, and 陳昱志. "Hybrid random walk model for social-based recommendation." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/44414823737098830352.

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碩士<br>臺灣大學<br>資訊工程學研究所<br>98<br>The concept of random walk (RW) has been widely applied in the design of recommendation systems. Compared to the popular collaborative-filtering approach, RW-based approaches are more effective in handling the locality problem and taking extra information, such as the relationships between items or users, into consideration. However, the traditional RW-based approach has a serious limitation in handling bi-directional opinions. In other words, the propagation of positive and negative information simultaneously in a graph is non-trivial using random walk. To addr
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SINGH, YOGENDRA. "A PERSONALIZED HYBRID MOVIE RECOMMENDATION SYSTEM FOR USERS." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15145.

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We describe a rating logical thinking approach to incorporating matter user reviews into Collaborative Filtering (CF) algorithms. The main motive of our approach is to use user preferences which is expressed in movie reviews and then convert such user’s preferences into some rating that may be understood by existing CF algorithms. The linguistics score of subjective sentence is fetched from SentiWordNet Library to calculate their sentiments as +ve, -ve or neutral based on the textual review. We’ve used SentiWordNet library as a dataset with two completely different approaches of alternatives c
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Yang, Tzu-Wei, and 楊子葳. "A Hybrid Preference-Aware Recommendation for Live Streaming Channels." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/95950586381053986201.

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Chung, Hao-Hsiang, and 鍾浩翔. "Learning Hybrid Poisson Aspect Model For Personalized Shopping Recommendation." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/12747747170772146994.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>90<br>Recommendations that really match customers' needs can boost sales. Researchers have proposed and evaluated many approaches for generating recommendations. In this thesis, we proposed a model-based collaborative approach, called Hybrid Poisson Aspect Model (HyPAM). HyPAM is a hybrid system combining two probabilistic models, cluster and aspect, which model the relationship between customer clusters and product types. Given a new customer and his/her shopping record, HyPAM can estimate his/her degree of
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Lin, Chung-Yu, and 林重佑. "A Study on LVQ Based Switching Hybrid Movie Recommendation." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/11873132375795364614.

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碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>100<br>The great development of Internet technology brings more and more people to use computers to extract abundant content from this platform by their high speed computing ability. To keep the most valued consumers, most corporations have launched to the electronic environment in order to provide personalized services to their consumers. Content-based filtering and collaborative filtering are widely used techniques in recommendation system. The former method analyzes used records from users to make recommendation. The latter one takes the advantage of user pref
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Huang, Chien-Cheng, and 黃建晟. "A Hybrid Approach of Customer Lifetime Value to Library Recommendation." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/31423208251762211735.

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碩士<br>玄奘大學<br>國際企業學系碩士班<br>96<br>With the rapid development of Internet, the library through the platform has provided a lot of electronic resources and several services for readers to get information. When readers query the information of books, they probably spend lots of time to find the required information. In the other hand, readers may not be very clear how to seek the information or books that they need. As a result, the frequency and the desire to use the library system are decreased. In this paper, we try to build a collaborative filtering recommended system based on customer lifetim
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Hung, Min-Cheng, and 洪旻呈. "A Hybrid Intelligence Mechanism for Group Investment on Portfolio Recommendation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8x593n.

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碩士<br>國立交通大學<br>資訊管理研究所<br>106<br>More and more people want to invest financial products by themselves rather than saving in the banks. Recently, participating in an investment club becomes a good choice for investors. It is likely more profitable to follow with financial experts in investing club as they can learn how to select stock and get greater positive ROI. But many of investment clubs have low return of rate from financial crisis in 2007-2008. In this study, we want to propose a recommendation mechanism that combine collective intelligence and a special type of recurrent neural network
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Chuck, Chen. "A Hybrid Recommendation System with Vector Profile Based on Fuzzy Clustering." 2002. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0009-0112200611342828.

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Chen, Shuan-Han, and 陳萱翰. "The application of a hybrid recommendation system on on-line shopping." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/26s8f4.

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碩士<br>國立東華大學<br>資訊工程學系<br>102<br>With the advance of Internet, people can search and purchase what they need from the Internet even in the home. However, in the age of information explosion, how users can find their interested goods becomes a major problem to be solved. Although there are many auction websites to support this service, their performances are not very good. Users also can’t stay in front of the computer on twenty-four hours a day to browse the website. Therefore, how to face with the information explosion and provide the user convenience becomes our concerned problem. A recommen
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Lai, Huan-Wen, and 賴奐文. "Developing a Hybrid Recommendation System with the Consideration of Order Effect." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/11618700299285099032.

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碩士<br>國立中正大學<br>資訊管理學系暨研究所<br>101<br>Recommender system has been successfully applied for e-commerce sites for a few years. Recommender system can be classified into two categories, content-based filtering and collaborative filtering. Content-based filtering recommends interesting items to the target user by analyzing their content features. On the other hand, collaborative filtering makes recommendations based on similar users’ opinions. However, each of them has its own advantages and disadvantages. Hence, many hybrid recommender systems have been proposed. The prediction accuracy of recomme
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Lee, Wang-Jung, and 李宛蓉. "A Hybrid of Sequential Rules and Collaborative Filtering for Product Recommendation." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/10683024951188371694.

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碩士<br>國立交通大學<br>資訊管理研究所<br>94<br>Customers’ purchase behavior may vary over time. Traditional Collaborative Filtering (CF) methods use similar customers’ purchase behavior to provide recommendations to the target customer, without considering customers’ purchase behavior over time. The sequential rule-based recommendation method mainly analyzes customers’ purchase behavior over time to extract sequential rules with the form: purchase behavior over past periods => purchase behavior at current period. If a target customer’s purchase behavior over past periods is similar to the conditional part o
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Chen, Chuck, and 陳羿逞. "A Hybrid Recommendation System with Vector Profile Based on Fuzzy Clustering." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/31655568375136262539.

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碩士<br>元智大學<br>資訊工程學系<br>90<br>Rapid development of the Internet makes users differentiating what information is really needed more difficult. To cope with the problems of information overloading and low signal to noise ratio, a number of solutions based on information filtering, mainly content-based filtering, collaborative filtering and hybrid filtering, have been applied to develop an adaptive web site. In this thesis, we present a hybrid filtering mechanism into the development of a recommendation system for e-Learning. The web pages and users’ logs are represented into vector pr
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Huang, Wen-Yi, and 黃文益. "The Design of A Hybrid Information Recommendation System for Music CD." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/34014268708168574306.

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碩士<br>國立屏東商業技術學院<br>資訊管理系<br>95<br>Selecting music CDs is a hard job since it is a matching work between our changing preferences and kinds of music. Therefore, a information recommendation system can be helpful for users to selecting their music CDs. This study aims to develop a hybrid information recommendation system which combines the collaborative filtering technique and the content-based filtering technique. The collaborative filtering technique can filter music CDs based on the preferences of near neighbors. And the content-based filtering will filter music CDs at the second stage based
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Wang, Jhen-Yuan, and 王振遠. "A solution to the diversity problem using a hybrid recommendation system." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/76635827232231044566.

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碩士<br>國立東華大學<br>資訊工程學系<br>101<br>The most important thing in any recommendation system is to find the customers’ interests. Due to the customers having a lot of interests, a recommendation list must have many types of products to meet the customers’ interests, and we call this diversity. In the past years, many researches have focused on improving the accuracy of recommendation results. While some researchers have begun to focus on recommendation diversity, others have proposed methods to solve the problems of diversity based on one similarity. In fact, the calculation of diversity has many ty
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NIRWAN, HITESH. "RECOMMENDATION BASED APPROACH USING FCM IN E-COMMERCE SYSTEM." Thesis, 2014. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15631.

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Aim of recommendation system is to predict the level of preferences of users towards some items, with the purpose of suggesting ones that they may like, among the sets of items they have not visited yet. In other words the aim of recommendation system is to improve the user experience by suggesting items the user may purchase. The recommendation system targets the personalization aspects of each user. It provides the items in the recommendation list according to particular customers and improve the user experience and for this it exploits the user specific interest and the preferences by
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Yi-LunWu and 吳怡倫. "A Hybrid Recommendation Model Based on Probabilistic Matrix Factorization and Sentiment Analysis." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/13262910035594225002.

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碩士<br>國立成功大學<br>資訊管理研究所<br>104<br>In recommender systems, probabilistic matrix factorization model has been examined and showed to give promising recommendation, but it only takes ratings into consideration and has long been criticized for its inability to provide explainable recommendation. On the other hand, because we can unearth users' preferred features from review text, review text should be viewed as an essential element in recommender systems. And when it comes to understanding users' preferred features, sentiment analysis methods report great performance on extracting product feature
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