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JAAMAS 2026

Adaptive Web Site Agents

Journal Article OriginalPaper Artificial Intelligence ยท Multi-Agent Systems

Abstract

Abstract We discuss the design and evaluation of a class of agents that we call adaptive web site agents. The goal of such an agent is to help a user find additional information at a particular web site, adapting its behavior in response to the actions of the individual user and the actions of other visitors to the web site. The agent recommends related documents to visitors and we show that these recommendations result in increased information read at the site. It integrates and coordinates among different reasons for making recommendations including user preference for subject area, similarity between documents, frequency of citation, frequency of access, and patterns of access by visitors to the web site. We argue that this information is best used not to change the structure or content of the web site but rather to change the behavior of an animated agent that assists the user.

Authors

Keywords

  • recommendation systems
  • personalization

Context

Venue
Autonomous Agents and Multi-Agent Systems
Archive span
2005-2026
Indexed papers
940
Paper id
59486249315779236
v2026.09.13