DocumentCode
2060477
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
fYear
2010
fDate
Nov. 29 2010-Dec. 1 2010
Firstpage
918
Lastpage
922
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
Conference_Location
Cairo
Print_ISBN
978-1-4244-8134-7
Type
conf
DOI
10.1109/ISDA.2010.5687072
Filename
5687072
Link To Document