opinion extraction and classification
Opinion Extraction and Classification Based on Semantic Similarities
Elkhlifi, Aymen (Paris-Sorbonne University) | Bouchlaghem, Rihab (LARODEC, ISG de Tunis) | Faiz, Rim
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.