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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Mining Market Trend from Blog Titles Based on Lexical Semantic Similarity
verfasst von : Fei Wang, Yunfang Wu
Erschienen in: Computational Linguistics and Intelligent Text Processing
Verlag: Springer Berlin Heidelberg
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Today blog has become an important medium for people to post their ideas and share new information. And the market trend of pricing Up/Down always draws people’s attention. In this paper, we make a thorough study on mining market trend from blog titles in the field of housing market and stock market, based on lexical semantic similarity. We focus on the automatic extraction and construction of Chinese Up/Down verb lexicon, by using both Chinese and Chinese-English bilingual semantic similarity. The experimental results show that verb lexicon extraction based on semantic similarity is of great use in the task of mining public opinions on market trend, and that the performance of applying English similar words to Chinese verb lexicon extraction is well compared with using Chinese similar words.