University of Twente Student Theses


Hybrid Content-Based Collaborative-Filtering Music Recommendations

Siles Del Castillo, Hugo (2007) Hybrid Content-Based Collaborative-Filtering Music Recommendations.

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Abstract:Recommendation of music is emerging with force nowadays due to the huge amount of music content and because users normally do not have the time to search through these collections looking for new items. The main purpose of a recommendation system is to estimate the user’s preferences and present him with some items that he does not know yet. Currently, most of the audio recommendation systems can be classified in two major kinds: recommendation systems based on collaborative filtering techniques and content based recommendation system. While both kinds of systems have good characteristics, they fail to provide good recommendation is specific situations. Recently a new kink of recommendation systems is emerging, hybrid content-based collaborative-filtering recommendation systems. The main objective of this thesis is to try to probe that the main disadvantages of content-based and collaborative filtering recommendation methods can be solver using hybrid methods. In order to do this we built a hybrid content-based collaborative filtering recommendation system. This hybrid system possesses the best characteristics of both methods and produce better results than each method individually. To achieve our goal we will also present a research on current content-based and collaborative methods in such a way that we will be able to fin out advantages and disadvantages of them
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science MSc (60300)
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