Unapparent information revelation: a concept chain graph approach.

Proceedings of the 14th ACM international conference on Information and knowledge management(2005)

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摘要
Information generated by multiple authors working independently at different times when analyzed synergistically reveals more information than apparent. For example, a traditional search for connections between the trucking industry and Iraqi banks may not produce any documents mentioning both. However, a search that follows trails of associations across documents may suggest a connection between an auto parts manufacturer who exports to Iraq, and an Iraqi bank providing loans to buy cars. The work described here extends link analysis based on named entities and labeled relationships to general concepts and unnamed associations. Unapparent Information Revelation involves finding chains connecting concepts across documents: it uses a new representation formalism called Concept Chain Graphs.
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