Survey of Text Mining
Fast discovery of connection subgraphs
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
InfoXtract: a customizable intermediate level information extraction engine
SEALTS '03 Proceedings of the HLT-NAACL 2003 workshop on Software engineering and architecture of language technology systems - Volume 8
Mining concept associations for knowledge discovery through concept chain queries
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Mining semantic relationships between concepts across documents incorporating wikipedia knowledge
ICDM'13 Proceedings of the 13th international conference on Advances in Data Mining: applications and theoretical aspects
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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.