Structure and semantics for expressive text kernels

  • Authors:
  • Stephan Bloehdorn;Alessandro Moschitti

  • Affiliations:
  • University of Karlsruhe, Karlsruhe, Germany;University of Trento, Povo di Trento, Italy

  • Venue:
  • Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
  • Year:
  • 2007

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Abstract

Several Text Categorization applications require a representation beyond the standard bag-of-words paradigm. Kernel-based learning has approached this problem by (i) considering information about syntactic structure or by (ii) incorporating knowledge about the semantic similarity of term features. We propose a generalized framework consisting of a family of kernels that jointly incorporate syntactic and semantic similarity and demonstrate the power of this approach in a series of experiments.