Combining Content-Based and Collaborative Filters in an Online Newspaper (1999)
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BibTeX
@MISC{Claypool99combiningcontent-based,
author = {Mark Claypool and Anuja Gokhale and Tim Miranda and Pavel Murnikov and Dmitry Netes and Matthew Sartin},
title = {Combining Content-Based and Collaborative Filters in an Online Newspaper},
year = {1999}
}
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Abstract
The explosive growth of mailing lists, Web sites and Usenet news demands effective filtering solutions. Collaborative filtering combines the informed opinions of humans to make personalized, accurate predictions. Content-based filtering uses the speed of computers to make complete, fast predictions. In this work, we present a new filtering approach that combines the coverage and speed of content-filters with the depth of collaborative filtering. We apply our research approach to an online newspaper, an as yet untapped opportunity for filters useful to the wide-spread news reading populace. We present the design of our filtering system and describe the results from preliminary experiments that suggest merits to our approach.
