Automated Rule Selection for Aspect Extraction in Opinion Mining

@inproceedings{Liu2015AutomatedRS,
  title={Automated Rule Selection for Aspect Extraction in Opinion Mining},
  author={Qian Liu and Zhiqiang Gao and Bing Liu and Yuanlin Zhang},
  booktitle={IJCAI},
  year={2015}
}
Aspect extraction aims to extract fine-grained opinion targets from opinion texts. Recent work has shown that the syntactical approach, which employs rules about grammar dependency relations between opinion words and aspects, performs quite well. This approach is highly desirable in practice because it is unsupervised and domain independent. However, the rules need to be carefully selected and tuned manually so as not to produce too many errors. Although it is easy to evaluate the accuracy of… CONTINUE READING
Highly Cited
This paper has 42 citations. REVIEW CITATIONS

From This Paper

Figures, tables, results, connections, and topics extracted from this paper.
22 Extracted Citations
58 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 22 extracted citations

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 58 references

In KDD ’04

  • Minqing Hu, Bing Liu. Mining, summarizing customer reviews
  • pages 168–177,
  • 2004
Highly Influential
7 Excerpts

In IJCAI ’13

  • Kang Liu, Liheng Xu, Yang Liu, Jun Zhao. Opinion target extraction using partially-su model
  • pages 2134–2140,
  • 2013
Highly Influential
4 Excerpts

In ACL ’14

  • Zhiyuan Chen, Arjun Mukherjee, Bing Liu. Aspect extraction with automated prior knowle learning
  • pages 347–358,
  • 2014
1 Excerpt

In COLING ’14

  • Yanyan Zhao, Wanxiang Che, Honglei Guo, Bing Qin, Zhong Su, Ting Liu. Sentence compression for target-polarity word extraction
  • pages 1360–1369,
  • 2014
1 Excerpt

Similar Papers

Loading similar papers…