Exploiting Wikipedia for Directional Inferential Text Similarity

  title={Exploiting Wikipedia for Directional Inferential Text Similarity},
  author={Chee Wee Leong and S. Hassan},
  journal={Fifth International Conference on Information Technology: New Generations (itng 2008)},
In natural languages, variability of semantic expression refers to the situation where the same meaning can be inferred from different words or texts. Given that many natural language processing tasks nowadays (e.g. question answering, information retrieval, document summarization) often model this variability by requiring a specific target meaning to be inferred from different text variants, it is helpful to capture text similarity in a directional manner to serve such inference needs. In this… CONTINUE READING
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Key Quantitative Results

  • Through experiments, we show that our Wikipedia-based metric performs significantly better when applied to a standard evaluation dataset, with a reduction in error rate of 16.1% over the random metric baseline.


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