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Paraphrase Recognition using Neural Network Classification

by Anupriya Rajkumar, A.Chitra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 29
Year of Publication: 2010
Authors: Anupriya Rajkumar, A.Chitra
10.5120/576-574

Anupriya Rajkumar, A.Chitra . Paraphrase Recognition using Neural Network Classification. International Journal of Computer Applications. 1, 29 ( February 2010), 42-47. DOI=10.5120/576-574

@article{ 10.5120/576-574,
author = { Anupriya Rajkumar, A.Chitra },
title = { Paraphrase Recognition using Neural Network Classification },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 29 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 42-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number29/576-574/ },
doi = { 10.5120/576-574 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:42:00.903078+05:30
%A Anupriya Rajkumar
%A A.Chitra
%T Paraphrase Recognition using Neural Network Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 29
%P 42-47
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Paraphrasing refers to conveying the same content in several ways. The successful recognition of paraphrases is crucial to various natural language processing tasks such as Information Extraction, Document Summarization, Question Answering etc. Several techniques have been employed for paraphrase recognition using lexical, syntactic and semantic features. Many of these systems have been tested on the MicroSoft Research Paraphrase Corpus. But the performance of these systems has scope for further improvement. Since neural network architectures model the human brain structure which excels at natural language processing tasks, this paper presents a neural network classifier for recognizing paraphrases. A combination of lexical, syntactic and semantic features has been used to train a Back Propagation network. The system can be utilized for detecting similar sentences in applications such as Question Answering and detection of plagiarized content.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Paraphrase Recognition Lexical Syntactic Semantic features Neural Network Recognizer Back Propagation Network

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