NDLI: Paraphrase identification in short texts using grammar patterns

Content Provider	IEEE Xplore Digital Library
Author	Vaishnavi, V. Saritha, M. Milton, R.S.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Eng., SSN Coll. of Eng., Chennai, India (Vaishnavi, V.; Saritha, M.; Milton, R.S.)
Abstract	We can determine whether two texts are paraphrases of each other by finding out the extent to which the texts are similar. The typical lexical matching technique works by matching the sequence of tokens between the texts to recognize paraphrases, and fails when different words are used to convey the same meaning. We can improve this simple method by combining lexical with syntactic or semantic representations of the input texts. The present work makes use of syntactical information in the texts and computes the similarity between them using word similarity measures based on WordNet and lexical databases. The texts are converted into a unified semantic structural model through which the semantic similarity of the texts is obtained. An approach is presented to assess the semantic similarity and the results of applying this approach is evaluated using the Microsoft Research Paraphrase (MSRP) Corpus.
Sponsorship	IEEE Madras Sect.
Starting Page	472
Ending Page	477
File Size	389751
Page Count	6
File Format	PDF
ISBN	9781479910243
DOI	10.1109/ICRTIT.2013.6844249
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-25
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MSRP Natural languages Paraphrase Grammar Information technology Equations WordNet Semantics Lexical database Syntactics Market research Semantic similarity Semantic structural model
Content Type	Text
Resource Type	Article

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