Summary of the paper

Title Diversifiable Bootstrapping for Acquiring High-Coverage Paraphrase Resource
Authors Hideki Shima and Teruko Mitamura
Abstract Recognizing similar or close meaning on different surface form is a common challenge in various Natural Language Processing and Information Access applications. However, we identified multiple limitations in existing resources that can be used for solving the vocabulary mismatch problem. To this end, we will propose the Diversifiable Bootstrapping algorithm that can learn paraphrase patterns with a high lexical coverage. The algorithm works in a lightly-supervised iterative fashion, where instance and pattern acquisition are interleaved, each using information provided by the other. By tweaking a parameter in the algorithm, resulting patterns can be diversifiable with a specific degree one can control.
Topics Acquisition, Semantics, Textual Entailment and Paraphrasing
Full paper Diversifiable Bootstrapping for Acquiring High-Coverage Paraphrase Resource
Bibtex @InProceedings{SHIMA12.934,
  author = {Hideki Shima and Teruko Mitamura},
  title = {Diversifiable Bootstrapping for Acquiring High-Coverage Paraphrase Resource},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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