Title :
Automatic extraction and classification approach of opinions in texts
Author :
Bouchlaghem, Rihab ; Elkhlifi, Aymen ; Faiz, Rim
Author_Institution :
LARODEC, ISG de Tunis, Tunis, Tunisia
fDate :
Nov. 29 2010-Dec. 1 2010
Abstract :
In this paper, we present an approach to automatically extract and classify opinions in texts. We propose a similarity measurement calculating semantically distances between a word and predefined subgroups of seed words. We have evaluated our algorithm on the semantic evaluation company “SemEval 2007” corpus, and we obtained the best value of Precision and F1 62% and 61%. As an improvement of 20 % compared to others participants.
Keywords :
Internet; data mining; feature extraction; natural language processing; pattern classification; text analysis; word processing; SemEval 2007 corpus; automatic extraction; opinions classification; seed words; semantic evaluation company; similarity measurement; Natural Language Processing; Opinion Mining; Semantic Similarity;
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8134-7
DOI :
10.1109/ISDA.2010.5687072
