Collaborative Filtering without Explicit Feedbacks for Digital Recorders

Details Collaborative Filtering without Explicit Feedbacks for Digital Recorders Collaborative Filtering without Explicit Feedbacks for Digital Recorders

2011-01-17

arxiv.org/abs/1101.3341v1

Computer Science

Information Retrieval

Scientific paper

Recommendation is usually reduced to a prediction problem over the function $r(u_a, e_i)$ that returns the expected rating of element $e_i$ for user $u_a$. In the IPTV domain, we deal with an environment where the definitions of all the parameters involved in this function (i.e., user profiles, feedback ratings and elements) are controversial. To our knowledge, this paper represents the first attempt to run collaborative filtering algorithms without inner assumptions: we start our analysis from an unstructured set of recordings, before performing a data pre-processing phase in order to extract useful information. Hence, we experiment with a real Digital Video Recorder system where EPG have not been provided to the user for selecting event timings and where explicit feedbacks were not collected.

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