C4.5: programs for machine learning
C4.5: programs for machine learning
Agents that reduce work and information overload
Communications of the ACM
A softbot-based interface to the Internet
Communications of the ACM
Experience with a learning personal assistant
Communications of the ACM
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Referral Web: combining social networks and collaborative filtering
Communications of the ACM
Siteseer: personalized navigation for the Web
Communications of the ACM
Agent-mediated electronic commerce: issues, challenges and some viewpoints
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Communications of the ACM
Tailoring the interaction with users in electronic shops
UM '99 Proceedings of the seventh international conference on User modeling
Opportunistic exploration of large consumer product spaces
Proceedings of the 1st ACM conference on Electronic commerce
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Fundamentals of Database Systems
Fundamentals of Database Systems
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
An Adaptive Recommendation System without Explicit Acquisition of User Relevance Feedback
Distributed and Parallel Databases
Recommender systems: a market-based design
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
A market-based approach to recommender systems
ACM Transactions on Information Systems (TOIS)
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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Personal agents have been developed that assist a user with information processing needs by generating, filtering, collecting, or transforming information. On the other hand, internet stores are providing services customized by the needs and interests of individual customers. Such services can be viewed as ''seller's agents'' whose goal is to push merchandise and/or services on to the users. This leads us to believe that there is a growing need for deploying ''buyer's agents'' whose goal is to best serve the consumer's interests. The Internet contains a huge volume of information which can overwhelm a buyer. The buyers may often make misinformed decisions based on partial, outdated, irrelevant or incorrect information. We have identified several key functionalities of buyer's agents whose goal is to reduce information overload and improve relevancy and accuracy of information for consumers. In particular, such agents can make consumers aware of complex interactions between specified preferences and prevailing market conditions, provide differential analysis for decision support, and use domain ontologies to help the user reformulate queries to improve satisfaction with query results. We present SAATHI, a prototype buyer's agent that demonstrate some of these functionalities in an apartment locator domain.