Inferring user interest
Mark Claypool, David C. Brown, Phong Le, Makoto Waseda · IEEE Internet Computing · 2001
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.