Information discovery within organizations using the Athens system

Authors:
Nikhil Vats;David B. Skillicorn
Affiliations:
School of Computing, Queen's University, Kingston, Canada;School of Computing, Queen's University, Kingston, Canada
Venue:
CASCON '04 Proceedings of the 2004 conference of the Centre for Advanced Studies on Collaborative research
Year:
2004

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Abstract

The serendipitous discovery of novel information in the web is a challenging task. Existing retrieval tools, like search engines, can retrieve information about known topics. However, they cannot retrieve information about novel topics, that is topics whose existence is unknown to the user and which may be potentially interesting. We present Athens, a system for discovering novel information in the web. Athens comprises three fundamental components: closure to find the essential content of a set of search query terms; probing to create new contextualized queries for retrieving information of wider scope; and clustering to remove less relevant information. Given a set of initial query terms, the system repeats these steps twice to reach novel information relative to the initial query topic. This paper describes an application of the Athens system to web-based data for two organizations: IBM and Microsoft. We compare the novel information generated for the two organizations against a query and discuss the encouraging results obtained.