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 Cite-Seer as a source of information, that show the effectiveness of our approach. Copyright 2006 ACM.
A multi-agent system that facilitates scientific publications search / Birukou, A., Blanzieri, E., Giorgini, P.. - 2006:(2006), pp. 265-272. (Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Hakodate, jpn 2006) [10.1145/1160633.1160680].
A multi-agent system that facilitates scientific publications search
Birukou, A.;Blanzieri, E.;Giorgini, P.
2006-01-01
Abstract
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 Cite-Seer as a source of information, that show the effectiveness of our approach. Copyright 2006 ACM.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
