Zusammenfassung
With the merge of digital television (DTV) and the exponential growth
of broadcasting network, an overwhelmingly amount of information has
been made available to a consumer's home. Therefore, how to provide
consumers with the right amount of information becomes a challenging
problem. In this paper, we propose an electronic programming guide
(EPG) recommender based on natural language processing techniques, more
specifically, text classification. This recommender has been
implemented as a service on a home network that facilitates the
personalized browsing and recommendation of TV programs on a portable
remote device. Evaluations of our Maximum Entropy text classifier were
performed on multiple categories of TV programs, and a near 80\%
retrieval rate is achieved using a small set of training data.
Nutzer