Collaborative interface agents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
The ContactFinder agent: answering bulletin board questions with referrals
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Hybrid hill-climbing and knowledge-based methods for intelligent news filtering
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Collecting user access patterns for building user profiles and collaborative filtering
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
User population and user contributions to virtual publics: a systems model
GROUP '99 Proceedings of the international ACM SIGGROUP conference on Supporting group work
Human evaluation of Kea, an automatic keyphrasing system
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Journal of the American Society for Information Science and Technology
Oracles, Bards, and Village Gossips, or Social Roles and Meta Knowledge Management
Information Systems Frontiers
Enterprise Knowledge Management
Computer
Guest Editor's Introduction: Knowledge-Management Systems-Converting and Connecting
IEEE Intelligent Systems
A Knowledge-Based News Server Supporting Ontology-Driven Story Enrichment and Knowledge Retrieval
EKAW '99 Proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management
Design Issues for Agent-Based Resource Locator Systems
PAKM '02 Proceedings of the 4th International Conference on Practical Aspects of Knowledge Management
A Personalized Interface Agent with Feedback Evaluation
AMT '01 Proceedings of the 6th International Computer Science Conference on Active Media Technology
A Personal Agent for Bookmark Classification
PRIMA 2001 Proceedings of the 4th Pacific Rim International Workshop on Multi-Agents, Intelligent Agents: Specification, Modeling, and Applications
Using keyphrases as search result surrogates on small screen devices
Personal and Ubiquitous Computing
Contextual relevance feedback in web information retrieval
IIiX Proceedings of the 1st international conference on Information interaction in context
A group recommendation system with consideration of interactions among group members
Expert Systems with Applications: An International Journal
A novel collaborative filtering approach for recommending ranked items
Expert Systems with Applications: An International Journal
Content-based personalised recommendation in virtual shopping environment
International Journal of Business Intelligence and Data Mining
Feature-based recommendations for one-to-one marketing
Expert Systems with Applications: An International Journal
MAPIS, a multi-agent system for information personalization
Information and Software Technology
Coauthorship networks and academic literature recommendation
Electronic Commerce Research and Applications
The benefits of using mobile agents in distributed environments
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
A web personalized service based on dual GAs
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Applications of agent technology in communications: a review
Computer Communications
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InfoFinder is an intelligent agent that learns user information interests from sets of messages or other online documents that users have classified. While this problem has been addressed by a number of recent research initiatives, InfoFinder's approach is innovative in a number of ways. First, the agent uses heuristics to extract significant phrases from documents for learning rather than using statistical techniques. This enables it to learn highly general search criteria based on a small number of sample documents. Second, the agent's induction algorithm is based on the observation that sample documents in such an application will not be uniformly distributed, because of the fact that users will tend to classify positive examples while browsing while classifying negative examples only when the agent makes a bad recommendation. Third, the agent learns standard decision trees for each user category. These decision trees are easily transformed into search query strings for standard search systems rather than requiring specialized search engines, and are significantly more expressive than other representations such as positive and negative word lists.