WebIC: An Effective "Complete-Web" Recommender System
|Russ Greiner||University of Alberta||[Home Page]|
Notice: Hosted by Vinay Chaudhri.
Date: Thursday December 01, 2011 at 16:00
Location: EJ228 (SRI E building) (Directions)
Many web recommendation systems direct users to webpages, from a single website, that other similar users have visited. By contrast, our WebIC web recommendation system is designed to locate "information content (IC) pages" --- pages the current user needs to see to complete her task --- from essentially anywhere on the web. WebIC first extracts the "browsing properties" of each word encountered in the user's current click-stream --- eg, how often each word appears in the title of a page in this sequence, or in the "anchor" of a link that was followed, etc. It then uses a user- and site-independent model, learned from a set of annotated web logs acquired in a user study, to determine which of these words is likely to appear in an IC page. We discuss how to use these IC-words to find IC-pages, and demonstrate empirically that this browsing-based approach works effectively.
Joint work with Tingshao Zhu, Gerald Haeubl and Bob Price
Please arrive at least 10 minutes early in order to sign in and be escorted to the conference room. SRI is located at 333 Ravenswood Avenue in Menlo Park. Visitors may park in the visitors lot in front of Building E, and should follow the instructions by the lobby phone to be escorted to the meeting room. Detailed directions to SRI, as well as maps, are available from the Visiting AIC web page.