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Author:

Du, Yongping (Du, Yongping.) (Scholars:杜永萍) | He, Ming (He, Ming.)

Indexed by:

EI Scopus

Abstract:

Recognizing Textual Entailment (RTE) task is defined as recognizing, given two text fragments T(Text) and H (Hypothesis), whether the meaning of H can be inferred from T. This paper discusses multiple techniques to implement the task, including lexical matching, semantic matching and syntactic matching methods. Word overlap is the basic technology and the part-of-speech is applied for the improvement of lexical matching approach. WordNet resource is exploited for the semantic matching. Especially, the strict matching and fuzzy matching of dependency relations are used for implementing the syntactic matching method. Finally, the system has been evaluated on the data set of RTE-3, RTE-4 and RTE-5. We also explore the effect of different techniques on system performance. The best accuracy is 57.4% for 3-way task and 60.2% for 2-way task. Copyright © 2011 Binary Information Press.

Keyword:

Computational linguistics Text processing Syntactics Semantics Character recognition Natural language processing systems

Author Community:

  • [ 1 ] [Du, Yongping]Institute of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [He, Ming]Institute of Computer Science, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Computational Information Systems

ISSN: 1553-9105

Year: 2011

Issue: 7

Volume: 7

Page: 2403-2411

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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