DocumentCode :
1626105
Title :
Paraphrase identification of malayalam sentences - an experience
Author :
Mathew, Dinto ; Idicula, Sumam Mary
Author_Institution :
Dept. of Comput. Sci., CUSAT, India
fYear :
2013
Firstpage :
376
Lastpage :
382
Abstract :
Sentences with different structures may convey the same meaning. Identification of sentences with paraphrases plays an important role in text related research and applications. This work focus on the statistical measures and semantic analysis of Malayalam sentences to detect the paraphrases. The statistical similarity measures between sentences, based on symbolic characteristics and structural information, could measure the similarity between sentences without any prior knowledge but only on the statistical information of sentences. The semantic representation of Universal Networking Language(UNL), represents only the inherent meaning in a sentence without any syntactic details. Thus, comparing the UNL graphs of two sentences can give an insight into how semantically similar the two sentences are. Combination of statistical similarity and semantic similarity score results the overall similarity score. This is the first attempt towards paraphrases of malayalam sentences.
Keywords :
graph theory; natural language processing; statistical analysis; text analysis; Malayalam sentences; UNL graphs; paraphrase detection; paraphrase identification; semantic analysis; semantic representation; semantic similarity score; sentence identification; statistical measures; statistical similarity measures; statistical similarity score; structural information; text related research; universal networking language; Accuracy; Dictionaries; Indexes; Semantics; Syntactics; Semantic Textual Similarity(STS); Statistical Similarity; Universal Networking Language(UNL);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computing (ICoAC), 2013 Fifth International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3447-8
Type :
conf
DOI :
10.1109/ICoAC.2013.6921980
Filename :
6921980
Link To Document :
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