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An Adaptive User Profile for Filtering News Based on a User Interest Hierarchy

By Sarabdeep Singh, Michael Shepherd, Jack Duffy and Carolyn Watters

Abstract

A prototype system for the filtering and ranking of news items has been developed and a pilot test has been conducted. The user’s interests are modeled by a user interest hierarchy based on explicit user feedback with adaptive learning after each session. The system learned very quickly, reaching normalized recall values of over 0.9 within three sessions. When the user’s interests “drifted”, the system adapted but the speed with which it adapted seemed dependent on the amount of feedback provided by the user

Topics: BH. Information needs and information requirements analysis., CB. User studies., II. Filtering., HZ. None of these, but in this section.
Publisher: Richard B. Hill
Year: 2006
OAI identifier: oai:eprints.rclis.org:8789
Provided by: E-LIS repository

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