HYBRID MOVIE RECOMMENDERS BASED ON NEURAL NETWORKS AND DECISION TREES HYBRID MOVIE RECOMMENDERS BASED ON NEURAL NETWORKS AND DECISION TREES
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Mohammad Amin Rashidifar
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HYBRID MOVIE RECOMMENDERS BASED ON NEURAL NETWORKS AND DECISION TREES HYBRID MOVIE RECOMMENDERS BASED ON NEURAL NETWORKS AND DECISION TREES
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Anchor Academic Publishing
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9783954899371
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1
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CHF 31.20
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Anwendungs-Software
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English
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85
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kein Kopierschutz/DRM
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PC/MAC/eReader/Tablet
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PDF
The internet provides a lot of information to users. To help users find the items of their interest in this information overload, recommender systems have been developed. In this book we explored movie recommender systems based on three recommendation methods: content-based, collaborative filtering and a hybrid recommendation one based on the previous two. The algorithms that we used are the decision tree learning and the neural networks. The algorithms were implemented by using the data mining software Weka. To test these recommender systems, we combined the movie data from the Internet Movie Database and the rating data provided by Netflix. The results show that the proposed hybrid recommender systems does not perform better or worse than the content-based recommender systems and collaborative filtering recommender systems.