A Non-Invasive Learning Approach to Building Web User Profiles (1999)
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BibTeX
@MISC{Chan99anon-invasive,
author = {Philip K. Chan},
title = {A Non-Invasive Learning Approach to Building Web User Profiles},
year = {1999}
}
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Abstract
Introduction Recently researchers have started to make web browsers more adaptive and personalized. A personalized web browser caters to the user's interests and an adaptive one learns from the users' (potentially changing) access behavior. The goal is to help the user navigate the web. Lieberman's Letizia [13] monitors the user's browsing behavior, develops a user profile, and searches for potentially interesting pages for recommendations. The user profile is developed without intervention from the user (but the details of how that is performed is not clear in [13]). While the user is reading a page, Letizia searches, in a breadth-first manner, from that location, pages that could be of interest to the user. Pazzani et al.'s Syskill & Webert [18, 19] asks the user to rank pages in a specific topic. Based on the content and ratings of pages, the system learns a user profile that predicts if pages are of interest to th
