Improving Opinion Retrieval Based on Query-Specific Sentiment Lexicon
SCIE
SCOPUS
- Title
- Improving Opinion Retrieval Based on Query-Specific Sentiment Lexicon
- Authors
- Na S.-H; Lee Y; Nam S.-H; Lee J.-H.
- Date Issued
- 2009-04
- Publisher
- SPRINGER
- Abstract
- Lexicon-based approaches have been widely used for opinion retrieval due to their simplicity. However, no previous work has focused on the domain-dependency problem in opinion lexicon construction. This paper proposes simple feedback-style learning for query-specific opinion lexicon using the set of top-retrieved documents in response to a query. The proposed learning starts from the initial domain-independent general lexicon and creates a query-specific lexicon by re-updating the opinion probability of the initial lexicon based on top-retrieved documents. Experimental results on recent TREC test sets show that the query-specific lexicon provides a significant improvement over previous approaches, especially in BLOG-06 topics.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/35949
- DOI
- 10.1007/978-3-642-00958-7_76
- ISSN
- 0302-9743
- Article Type
- Article
- Citation
- LECTURE NOTES IN COMPUTER SCIENCE, vol. 5478, page. 734 - 738, 2009-04
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