Although content is fundamental to our music listening preferences, the leading performance in music recommendation is achieved by collaborative-filtering-based methods which exploit the similarity patterns in user’s listening history rather than the audio content of songs. Meanwhile, collaborative filtering has the well-known “cold-start” problem, i.e., it is unable to work with new songs that...

As the Internet has evolved, it has become an information, entertainment, retail, and communication source that millions of people use as a matter of routine. Given the diversity of views and the ability to post any kind of information on the Internet, very often, material that is considered objectionable can be easily accessed on the Web. This is particularly problematic when children are able...

In this paper, we present a new approach that is a synergy of itembased Collaborative Filtering (CF) and Case Based Reasoning (CBR) for personalized recommendations. We present a two-phase strategy: in phase I, we developed a context-sensitive item-based CF method that leverages the original past recommendations of peers via ratings performed on various information items. In phase II, we furthe...

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