Experimental Research on Correcting the Words Sequence of Product Features Extracted from Chinese Reviews
Lu Guang · Science Technology and Engineering · 2012
The Internet become used as a main medium for exchange of information and opinions,so Web has become an excellent source for gathering consumer opinions about products.However,up to now there are very few researches conducted on online reviews mining for Chinese text.In order to remedy this deficiency how to automatically mine product features is studied.The proposed method based on Apriori algorithm in the theory of association rules.The method computed the location probability value of words in frequent itemsets appeared in sentences,and then corrected the words sequence of the candidate product features.This made the mining results meet the requirements of standard syntax in Chinese language.The customer reviews from several popular website as the corpus dataset,and experimental findings indicated that the proposed method improves the performance of the product features extraction from Chinese customer reviews are downloaded.