Abstract
Personalized product reviews were presented by exploring the public comment data in order to study the method of personalized product review presentation based on crowd intelligence mining. Sentiment feature and topic distribution feature from user reviews were extracted and users were clustered into different groups based on the sentiment similarity and topic distribution similarity of their reviews. Experimental results show that our approach can reflect the similarity of users and find the same group. For a given user, reviews can be only presented from those who belong to the same group as oneself.
| Original language | English |
|---|---|
| Pages (from-to) | 675-681 |
| Number of pages | 7 |
| Journal | Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) |
| Volume | 51 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1 Apr 2017 |
Keywords
- Online comment
- Personalization
- Sentiment feature
- Similarity
- Topic model