Title :
Tagging online service reviews
Author :
Li, Suke ; Hao, Jinmei ; Chen, Zhong
Author_Institution :
Sch. of EECS, Peking Univ., Beijing, China
Abstract :
This paper proposes a tagging method that can highlight important service aspects for users who browse online service reviews. Experiments on service aspect ranking and review tagging show that the proposed method is effective for finding important aspects and can generate useful and interesting tags for reviews.
Keywords :
data mining; information services; online service reviews; review tagging method; service aspect ranking; Artificial neural networks; Tagging; World Wide Web; Service aspect tagging; opinion mining; service aspect ranking;
Conference_Titel :
Natural Language Processing and Knowledge Engineering (NLP-KE), 2010 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6896-6
DOI :
10.1109/NLPKE.2010.5587816
