Name
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. © 2012 IEEE. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/FSKD.2012.6234340 | FSKD |
Keywords | Field | DocType |
keyword extraction,product review,topic detection,internet,word recognition,electronic commerce,text analysis,filtering,noise,computational modeling,data mining,feature extraction,dictionaries | Correlative,Data mining,Information retrieval,Keyword extraction,Computer science,Filter (signal processing),Feature extraction,Product reviews,The Internet | Conference |
Volume | Issue | Citations |
null | null | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hua Zhao | 1 | 1 | 0.69 |
| Qingtian Zeng | 2 | 242 | 43.67 |
| Bingjie Sun | 3 | 0 | 0.34 |
| Weijian Ni | 4 | 14 | 8.09 |