Title :
Evolutionary approach for building efficient Paraphrase Recognizers
Author :
Chitra, A. ; Rajkumar, Anupriya
Author_Institution :
Dept. of Comput. Sci. & Eng., PSG Coll. of Technol., Coimbatore, India
Abstract :
Paraphrasing involves the restatement of a given text to convey the same intent. Paraphrase Recognition systems typically rely on lexical, syntactic and semantic features extracted from the candidate texts to identify equivalence. Though several Paraphrase Recognition systems exist, the performance of these systems has scope for further improvement. This paper reports the work done in designing an efficient Paraphrase Recognition system by using a Support Vector Machine Classifier coupled with Genetic Algorithm based Feature Selection. The developed paraphrase recognizer has exhibited comparable accuracy to the original approach by using only half the number of features.
Keywords :
genetic algorithms; natural language processing; pattern classification; support vector machines; text analysis; candidate texts; evolutionary approach; feature selection; genetic algorithm; paraphrase recognition systems; support vector machine classifier; Accuracy; Feature extraction; Genetic algorithms; Semantics; Support vector machines; Syntactics; Training; Genetic Algorithms; Paraphrase Recognition; Support Vector Machines;
Conference_Titel :
Information and Communication Technologies (WICT), 2011 World Congress on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4673-0127-5
DOI :
10.1109/WICT.2011.6141324