Title :
Research on recognition of the emotional tendencies in web data mining
Author :
Yang Zi-Rong ; Zeng Zhen ; Chen Jing-Hao
Author_Institution :
Sch. of Inf., Guizhou Financial & Econ. Inst., Guiyang, China
Abstract :
In the research of text emotional classification, although the method based on using characteristic words list and affective words list to identify the text emotional tendencies is simple and quick, but the accuracy is often poor. That´s more the method cannot judgment the rhetorical relations. To solve this problem, this paper from the semantic comprehension point of view, using the dependency parsing method to process the sentiment phrases, feature phrase and negative sentence, and makes the text emotional classification possible. The experimental results show that this method can meet the practical need.
Keywords :
Internet; data mining; emotion recognition; text analysis; Web data mining; affective words list; characteristic words list; dependency parsing method; emotion recognition; feature phrase; negative sentence; semantic comprehension point; sentiment phrases; text emotional classification; text emotional tendencies; Accuracy; Algorithm design and analysis; Feature extraction; Grammar; Semantics; Syntactics; XML; Dependency Parsing; data mining; emotional tendencies; recognition of the emotional;
Conference_Titel :
Business Management and Electronic Information (BMEI), 2011 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-61284-108-3
DOI :
10.1109/ICBMEI.2011.5920957