A Multi-Agent System that Facilitates Scientific Publications Search

@inproceedings{birukou-et-al:aamas06, 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 CiteSeer as a source of information, that show the effectiveness of our approach.}, author = {Birukou, Aliaksandr and Blanzieri, Enrico and Giorgini, Paolo }, booktitle = {AAMAS '06: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems}, citeulike-article-id = {696928}, keywords = {bibliography-management, bibtex, citeseer, implicit\_culture, information\_filtering, intelligent\_agents, mas, papers, publications, relevance\_feedback, search}, month = {May}, pages = {265--272}, posted-at = {2006-06-15 09:58:26}, priority = {0}, publisher = {ACM Press}, title = {A Multi-Agent System that Facilitates Scientific Publications Search}, url = {http://dit.unitn.it/\~{}birukou/publications/papers/200605aamas.pdf}, year = {2006} }

TY - CONF ID - birukou-et-al:aamas06 L3 - citeulike-article-id:696928 TI - A Multi-Agent System that Facilitates Scientific Publications Search T2 - AAMAS '06: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems SP - 265 EP - 272 PB - ACM Press N2 - 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. KW - bibliography-management KW - bibtex KW - citeseer KW - implicit_culture KW - information_filtering KW - intelligent_agents KW - mas KW - papers KW - publications KW - relevance_feedback KW - search AU - Birukou, Aliaksandr AU - Blanzieri, Enrico AU - Giorgini, Paolo PY - 2006/05// UR - http://dit.unitn.it/~birukou/publications/papers/200605aamas.pdf ER -