Journal
KNOWLEDGE-BASED SYSTEMS
Volume 146, Issue -, Pages 203-214Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2018.02.004
Keywords
Online travel; DWWP; Chinese new words detection; Sentiment lexicon; Word propagation
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Funding
- National Natural Science Foundation of China [91546201, 71331005, 71501175]
- Shandong Independent Innovation and Achievement Transformation Special Fund of China [2014ZZCX03302]
- Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences
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Online travel has developed dramatically during the past three years in China. This results in a large amount of unstructured data like tourism reviews from which it is hard to extract useful knowledge. In this paper, a DWWP system consisting of domain-specific new words detection (DW) and word propagation (WP) is presented. DW deals with the negligence of user-invented new words and converted sentiment words by means of AMI (Assembled Mutual Information). Inspired by social networks, the new method WP incorporates manually calibrated sentiment scores, semantic and statistical similarity information, which improves the quality of sentiment lexicon in comparison with existing data-driven methods. Experimental results show that DWWP improves seventeen percentage points compared with graph propagation and four percentage points compared with label propagation in terms of accuracy on Dataset I and Dataset II, respectively. (C) 2018 Published by Elsevier B.V.
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