论文信息 - Opinion Extraction and Classification Based on Semantic Similarities

Opinion Extraction and Classification Based on Semantic Similarities

This paper presents an automatic extraction and classification approach of opinions in texts. Therefore, we propose a similarity measurement calculating semantically similarities between a word and predefined subgroups of seed words. We have evaluated our approach on the semantic evaluation company “SemEval 2007” corpus, and we obtained promising results: the best value of Precision, 62%; and F1, 61%; as an improvement of 20 % compared to the participant systems.

Rim Faiz | Aymen Elkhlifi | Rihab Bouchlaghem

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