A Cognitive Model for Mining Latent Semantics in Unstructured Text

  • Rachakonda A
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Abstract

A cognitive model for mining latent semantics in unstructured text is described. The approach is to understand the formation of lexical semantics in humans from a cognitive standpoint and abstract this process onto a machine. A 3-layer model of latent semantics is proposed which helps define certain semantic associations as understood by humans. These associations are then systematically reduced to properties of term cooccurrences through a series of hypotheses. The hypotheses are confirmed through user evaluation of the resultant semantics. This work focuses on three latent semantic associations viz., topical anchors, semantic siblings and topical markers to explain the model.\r

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APA

Rachakonda, A. R. (2012). A Cognitive Model for Mining Latent Semantics in Unstructured Text. In VLDB PhD Workshop. Istanbul.

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