An Effective Complete-Web Recommender System

11 years 7 months ago
An Effective Complete-Web Recommender System
There are a number of recommendation systems that can suggest the webpages, within a single website, that other (purportedly similar) users have visited. By contrast, our goal is a system that can recommend "information content" (IC) pages -- i.e., pages that contain information relevant to the user -- from anywhere in the web. This paper describes how we addressed this challenge, We first collected a number of annotated user sessions, whose pages each include a bit indicating whether it was IC. Our system, ICPF, then used this collection to learn the characteristics of words that appear in such IC-pages, in terms of the word's "browsing features" (e.g., did the user follow links whose anchor included this word, etc.). This paper describes the ICPF system, as well as a tool (AIE) we developed to help users annotate their sessions, and a study we performed to collect these annotated sessions. We also present empirical data that validate the effectiveness of thi...
Gerald Häubl, Russell Greiner, Tingshao Zhu
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2003
Where WWW
Authors Gerald Häubl, Russell Greiner, Tingshao Zhu
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