Predicting Task-Specific Webpages for Revisiting

With the increased use of the web has come a corresponding increase in information overload that users face when trying to locate specific webpages, especially as a majority of visits to webpages are revisits. While automatically created browsing history lists offer a potential low-cost solution to re-locating webpages, even short browsing sessions generate a glut of webpages that do not relate to the user's information need or have no revisit value. We address how we can better support web users who want to return to information on a webpage that they have previously visited by building more useful history lists. The paper reports on a combination technique that semi-automatically segments the webpage browsing history list into tasks, applies heuristics to remove webpages that carry no intrinsic revisit value, and uses a learning model, sensitive to individual users and tasks, that predicts which webpages are likely to be revisited again. We present results from an empirical eva...

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Arwen Twinkle Lettkeman, Simone Stumpf, Jed Irvine, Jonathan L. Herlocker
• Keywords: AAAI 2006, History Lists, Intelligent Agents, Revisit Value, Webpages