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ABSTRACT
Title |
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A Knowledge Based Approach for Recognizing Textual Entailment for Natural Language Inference using Data Mining |
Authors |
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Dr. Arti Arya, Vishwanath Yaligar, Ramya D. Prabhu, Ramya Reddy, Rohith Acharaya |
Keywords |
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Recognizing Text Entailment (RTE), natural
language processing,data ( text) mining, knowledge base. |
Issue Date |
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September 2010 |
Abstract |
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Recognizing Textual Entailment (RTE) is a relatively
new problem necessary for Natural Language Understanding
(NLU) and Automated Knowledge Discovery. Natural Language
Inference has dealt with approaches like the bag of words
approach, formal methods (First order Logic) and pattern
relation extraction which usually do not show satisfactory results.
In this paper, Knowledge based approach has been proposed,
utilizing data mining concepts on large text which is
appropriately classified. Different Lexical resources like
WordNet, VerbNet, ConceptNet have been integrated into a rich
knowledge base, to provide semantics and structural information
on English words. The data mined is used by an Inference system
to give the output to the problem. The complete concept
presented in the paper has been implemented in the form of a
movie search engine wherein the knowledge based RTE concept
has been employed on “summaries or plots of the movies”
internally to get best possible classification of the movies. The
experiments have shown encouraging results, reduced the time of
search and provided more accurate results. To the best of our
knowledge, it is the first time that RTE concept has been
implemented to Information Search in the form of Movie Search
Engine.
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Page(s) |
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2133-2140 |
ISSN |
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0975–3397 |
Source |
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Vol. 2, Issue.6 |
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