DocumentCode :
2553186
Title :
Hierarchical product review detection based on keyword extraction
Author :
Zhao Hua ; Zeng Qingtian ; Sun Bingjie ; Ni Weijian
Author_Institution :
Coll. of Inf. Sci. & Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1299
Lastpage :
1302
Abstract :
Product reviews are very important for the sellers to make correct decisions. In order to help sellers detect the product reviews newly appearing in Internet, we propose a hierarchical product review detection method based on the keyword extraction. Taking the characteristic of the product reviews into account, this method firstly extracts the candidate keywords, and then filters out noise keywords based on the rules. And then extend these keywords based on the correlative words recognition. This paper finally realizes the hierarchical product review detection method based on these keywords. The experimental results show that the method proposed in this paper is successful.
Keywords :
Internet; electronic commerce; information filtering; marketing data processing; text analysis; Internet; correlative words recognition; hierarchical product review detection; keyword extraction; noise keyword filter; seller; topic detection; Computational modeling; Data mining; Dictionaries; Feature extraction; Filtering; Internet; Noise; Keyword Extraction; Product Review; Topic Detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6234340
Filename :
6234340
Link To Document :
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