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Compositionality in Quantitative Semantics. A Theoretical Perspective on Text Mining

  • Alexander Mehler
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 209)

Abstract

This chapter introduces a variant of the principle of compositionality in quantitative text semantics as an alternative to the bag-of-features approach. The variant includes effects of context-sensitive interpretation as well as processes of meaning constitution and change in the sense of usage-based semantics. Its starting point is a combination of semantic space modeling and text structure analysis. The principle is implemented by means of a hierarchical constraint satisfaction process which utilizes the notion of hierarchical text structure superimposed by graph-inducing coherence relations. The major contribution of the chapter is a conceptualization and formalization of the principle of compositionality in terms of semantic spaces which tackles some well known deficits of existing approaches. In particular this relates to the missing linguistic interpretability of statistical meaning representations.

Keywords

Text Component Lexical Item Latent Semantic Analysis Semantic Space Integration Hierarchy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2007

Authors and Affiliations

  • Alexander Mehler
    • 1
  1. 1.Bielefeld UniversityBielefeld

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