Agents that reduce work and information overload
Communications of the ACM
Communications of the ACM
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
E-commerce and the information market
Communications of the ACM
Recommendation systems: a probabilistic analysis
Journal of Computer and System Sciences - Special issue on Internet algorithms
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Just-in-time information retrieval agents
IBM Systems Journal
IEEE Transactions on Knowledge and Data Engineering
The Long Tail: Why the Future of Business Is Selling Less of More
The Long Tail: Why the Future of Business Is Selling Less of More
Enterprise Service Bus
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Restful web services
Programming collective intelligence
Programming collective intelligence
Advanced technologies in e-tourism
ACS'09 Proceedings of the 9th WSEAS international conference on Applied computer science
Business intelligence gap analysis: a user, supplier and academic perspective
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
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The world-wide-web (WWW) today consists of distinct, isolated islands of data and metadata. In the near future we expect the availability of a critical mass of data and metadata for use by intelligent agents that act on behalf of human users. These agents would identify, propose and capture new opportunities to assist human users in satisfying their goals, by traversing and acting on this semantically rich and abundant information. We envision a new class of agents, their networks and their communities that exist for the sole purpose of serving as their human "master's" Advocates - Advocate Agents. Advocate Agents learn a human's goals and preferences, collaborate with other agents, mine semantic content, identify new opportunities for action, propose them and finally transact them, while always keeping the human "in-the-loop." This paper discusses this class of distributed, intelligent, Advocate Agents, their potential uses, and proposed architectures and techniques that provide a conceptual framework for these networked agent societies to collaborate in the achievement of their human user's goals.