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Different Models and Approaches of Textual Entailment Recognition

by Mohamed H. Haggag, Marwa M.A. ELFattah, Ahmed Mohammed Ahmed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 1
Year of Publication: 2016
Authors: Mohamed H. Haggag, Marwa M.A. ELFattah, Ahmed Mohammed Ahmed
10.5120/ijca2016909667

Mohamed H. Haggag, Marwa M.A. ELFattah, Ahmed Mohammed Ahmed . Different Models and Approaches of Textual Entailment Recognition. International Journal of Computer Applications. 142, 1 ( May 2016), 32-39. DOI=10.5120/ijca2016909667

@article{ 10.5120/ijca2016909667,
author = { Mohamed H. Haggag, Marwa M.A. ELFattah, Ahmed Mohammed Ahmed },
title = { Different Models and Approaches of Textual Entailment Recognition },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 1 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 32-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number1/24863-2016909667/ },
doi = { 10.5120/ijca2016909667 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:43:48.110118+05:30
%A Mohamed H. Haggag
%A Marwa M.A. ELFattah
%A Ahmed Mohammed Ahmed
%T Different Models and Approaches of Textual Entailment Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 1
%P 32-39
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Variability of semantic expression is a fundamental phenomenon of a natural language where same meaning can be expressed by different texts. The process of inferring a text from another is called textual entailment. Textual Entailment is useful in a wide range of applications, including question answering, summarization, text generation, and machine translation. The recognition of textual entailment is one of the recent challenges of the Natural Language Processing (NLP) domain. This paper summarizes key ideas from the area of textual entailment recognition by considering in turn the different recognition models. The paper points to prominent testing data, training data, resources and Performance Evaluation for each model. Also this paper compares between textual entailment models according to the method which used, the result of each method and the strong and weakness of each method.

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Index Terms

Computer Science
Information Sciences

Keywords

Text entailment recognition WordNet Semantic analysis. Data Mining

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