Aliaksandr Birukou, Enrico Blanzieri, Paolo Giorgini

For people with non-ordinary interests, it is hard to search for information on the Internet because search engines are impersonalized and are more focused on “average” individuals with “standard” preferences. In order to improve web search for a community of people with similar but specific interests, we propose to use the implicit knowledge con- tained in the search behavior of groups of users. We developed a multi-agent recommendation system called Implicit, which supports web search for groups or communities of people. In Implicit, agents observe behavior of their users to learn about the “culture” of the community with specific interests. They facilitate sharing of knowledge about relevant links within the community by means of recommendations. The agents also recommend contacts, i.e., who in the community is the right person to ask for a specific topic. Experimental evaluation shows that Implicit improves the quality of the web search in terms of precision and recall.

Autonomous Agents and Multi-Agent Systems 24(1), pages 141-174, 2012, Springer Netherlands
@article{blanzieri-jaamas24,
Author = {Birukou, Aliaksandr and Blanzieri, Enrico and Giorgini, Paolo},
Doi = {10.1007/s10458-010-9148-z},
Issn = {1387-2532},
Journal = {Autonomous Agents and Multi-Agent Systems},
Number = 1,
Pages = {141--174},
Publisher = {Springer Netherlands},
Title = {{I}mplicit: A Multi-agent Recommendation System for Web Search},
Url = {http://www.springerlink.com/content/8x411v63w23460r2/},
Volume = 24,
Year = 2012}

    

Publication

— authors

Aliaksandr Birukou, Enrico Blanzieri, Paolo Giorgini

— status

published

— sort

article in journal

Venue

— journal

Autonomous Agents and Multi-Agent Systems

— volume/issue

24 (1)

— publication date

2012

— pages

141-174

URLs & IDs

original page

— DOI

10.1007/s10458-010-9148-z

— print ISSN

1387-2532

BibTeX

— BibTeX ID
blanzieri-jaamas24
— BibTeX category
article

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