Opinion Extraction and Classification Based on Semantic Similarities

نویسندگان

  • Aymen Elkhlifi
  • Rihab Bouchlaghem
  • Rim Faiz
چکیده

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.

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تاریخ انتشار 2011