A User Modeling System for Personalized Interaction and Tailored Retrieval in Interactive IR

Abstract

We present a user modeling system for personalized interaction and tailored retrieval that (1) tracks interactions over time, (2) represents multiple information needs, both short and long term, (3) allows for changes in information needs over time, (4) acquires and updates the user model automatically, without explicit assistance from the user, and (5) accounts for contextual factors such as topic familiarity and endurance of need. The proposed system contains three major classes of models: general behavioral, personal behavioral and topical. The general behavioral model describes how information search and use behavior can be used to identify and track information needs. The personal behavioral model characterizes an individual user's information search and use behavior with regard to document preference and states of knowledge. Finally, the topical model characterizes the user's information seeking needs. We describe how such a model can be used to personalize search interactions and tailor system responses to individuals across multiple information seeking sessions.