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A New Multiword Expression Metric and Its Applications

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Abstract

Multiword Expressions (MWEs) appear frequently and ungrammatically in natural languages. Identifying MWEs in free texts is a very challenging problem. This paper proposes a knowledge-free, unsupervised, and language-independent Multiword Expression Distance (MED). The new metric is derived from an accepted physical principle, measures the distance from an n-gram to its semantics, and outperforms other state-of-the-art methods on MWEs in two applications: question answering and named entity extraction.

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Authors and Affiliations

  1. State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Fan Bu & Xiao-Yan Zhu (Member, CCF)

  2. David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, N2L 3G1, Canada

    Ming Li (Fellow, ACM, IEEE)

Authors
  1. Fan Bu
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  2. Xiao-Yan Zhu
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  3. Ming Li
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Corresponding author

Correspondence to Fan Bu.

Additional information

This work was supported mainly by Canada’s IDRC Research Chair in Information Technology Program, under Grant No. 104519-006. It is also supported by the National Natural Science Foundation of China under Grant No. 60973104, the National Basic Research 973 Program of China under Grant No. 2007CB311003, NSERC Grant OGP0046506, Canada Research Chair’Program, MITACS, an NSERC Collaborative Grant, and Ontario’s Premier’s Discovery Award.

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Bu, F., Zhu, XY. & Li, M. A New Multiword Expression Metric and Its Applications. J. Comput. Sci. Technol. 26, 3–13 (2011). https://doi.org/10.1007/s11390-011-9410-0

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  • DOI: https://doi.org/10.1007/s11390-011-9410-0

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