Title :
Inferring user interest
Author :
Claypool, Mark ; Brown, David ; Le, Phong ; Waseda, Makoto
Abstract :
As the World Wide Web continues to grow, people find it impossible to access even a small portion of the information generated in a day from Usenet news, e-mail, and Web postings. Automated filters help us to prioritize and access only the information in which we´re interested. Because opinions differ about the importance or relevance of information, people need personalized filters. Implicit indicators captured while users browse the Web can be as predictive of interest levels as explicit ratings
Keywords :
information needs; information resources; online front-ends; relevance feedback; World Wide Web; automated filters; implicit ratings; personalized filters; relevance; Adaptive filters; Electronic commerce; Electronic mail; Information filtering; Information filters; Internet; Length measurement; Libraries; Web pages; Web sites;
Journal_Title :
Internet Computing, IEEE
DOI :
10.1109/4236.968829
