Font Size: a A A

Research On Extraction Patterns Of Product Description Words And Sentiment Words

Posted on:2011-07-05Degree:MasterType:Thesis
Country:ChinaCandidate:W J ZhaoFull Text:PDF
GTID:2178360308962269Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
With the rapid development of the World Wide Web, network has become a perfect platform to express and exchange of views. Nowadays, more and more users express their reviews on the products in the forum and other platforms. These reviews are very useful for consumers and product manufacturers. However, a mass of reviews makes it a hard task to get a just view. Therefore, product reviews analysis based on natural language processing technology is of great value. Extraction of product features and sentiment words from reviews is important processes in product reviews analysis.With the aid of theories and methods in computational linguistics, statistics, from the view of POS and syntax tree, we extract templates between product features and the corresponding sentiment words, develop new technologies and methods for extracting product features and the corresponding sentiment words from Chinese product reviews.This paper proposed a new algorithm to extract product features and the corresponding sentiment words from different domain Chinese product reviews based on the templates and domain related seed words. The experimental results show that the extraction algorithm required less manual intervention and gain good and stable performance in different domains. The extraction algorithm and the extracted templates are domain-independent.This paper is a departure from previous work in that:1) it utilizes the relationship between product features and the corresponding sentiment words to extract the two kinds of words mutually and iteratively; 2) The extraction algorithm of product features and the corresponding sentiment words is domain-independent. The performance of extraction algorithm is better than any previous work in this research domain. Without the use of any domain related training corpus and given several domain related seed words, the extraction algorithms can be applied to many different domains.
Keywords/Search Tags:product reviews analysis, product features, sentiment words, templates of POS tags, paths of parser tree
PDF Full Text Request
Related items