GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Proceedings of the 5th international conference on Intelligent user interfaces
Communications of the ACM
On the recommending of citations for research papers
CSCW '02 Proceedings of the 2002 ACM conference on Computer supported cooperative work
Discovering Relevant Scientific Literature on the Web
IEEE Intelligent Systems
UpLib: a universal personal digital library system
Proceedings of the 2003 ACM symposium on Document engineering
Ontological user profiling in recommender systems
ACM Transactions on Information Systems (TOIS)
Enhancing digital libraries with TechLens+
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
CiteSeer-API: towards seamless resource location and interlinking for digital libraries
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Implicit: an agent-based recommendation system for web search
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Emergence of global network property based on multi-agent voting model
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Cloning mechanisms to improve agent performances
Journal of Network and Computer Applications
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It is very difficult for beginners to define and find the most relevant literature in a research field. They can search on the web or look at the most important journals and conference proceedings, but it would be much better to receive suggestions directly from experts of the field. Unfortunately, this is not always possible and systems like CiteSeer and GoogleScholar become extremely useful for beginners (and not only). In this paper, we present an agent-based system that facilitates scientific publications search. Users interacting with their personal agents produce a transfer of knowledge about relevant publications from experts to beginners. Each personal agent observes how publications are used and induces behavioral patterns that are used to create more effective recommendations. Feedback exchange allows agents to share their knowledge and virtual communities of cloned experts can be created to support novice users. We present a set of experimental results, obtained using CiteSeer as a source of information, that show the effectiveness of our approach.