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Web Application of Recommender System
Koníček, Igor ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis describes creation of recommender system that is used in real server cbdb.cz. A~fully operational recommender system was developed using collaborative and content-based filtering techniques. Thanks to many user feedback, we were able to evaluate their opinion. Many recommended books were tagged as desirable. This thesis is extending current functionality of cbdb.cz with recommender system. This system uses its extensive database of ratings, users and books.
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Web Application of Recommender System
Hlaváček, Pavel ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with problems of recommender systems and their usage in web applications. There are three main data mining techniques summarized and individual approaches for recommendation. Main part of this thesis is a suggestion and an implementation of web applications for recommending dishes from restaurants. Algorithm for food recommending is designed and implemented in this paper. The algorithm deals with the problem of frequently changing items. The algorithm utilizes hybrid filtering technique which is based on content and knowledge. This filtering technique uses cosine vector similarity for computation.
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Systém pro doporučování filmů
Hnatovskyj, Vítek ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This work focuses on a movie recommendation system. First, the issue of recommendation systems in general is described, and the various types of these systems are outlined. The main goal is to implement a system that recommends relevant movies to the user based on their preferences. This system is hybrid, consisting of a content-based system and a collaborative filtering system. To test the system, a simple application is implemented, which is also described in this work. Subsequently, the system is evaluated using offline metrics and user testing.
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Web Application of Recommender System
Hlaváček, Pavel ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with problems of recommender systems and their usage in web applications. There are three main data mining techniques summarized and individual approaches for recommendation. Main part of this thesis is a suggestion and an implementation of web applications for recommending dishes from restaurants. Algorithm for food recommending is designed and implemented in this paper. The algorithm deals with the problem of frequently changing items. The algorithm utilizes hybrid filtering technique which is based on content and knowledge. This filtering technique uses cosine vector similarity for computation.
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Web Application of Recommender System
Koníček, Igor ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis describes creation of recommender system that is used in real server cbdb.cz. A~fully operational recommender system was developed using collaborative and content-based filtering techniques. Thanks to many user feedback, we were able to evaluate their opinion. Many recommended books were tagged as desirable. This thesis is extending current functionality of cbdb.cz with recommender system. This system uses its extensive database of ratings, users and books.
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