Recognition of Personal Objects in Netnews Oral Reviews

Author

Jie, Zhou ; Chen, Lin ; Bi-cheng Li

Author_Institution

Inf. Process. Dept., Inf. Technol. Inst., Zhengzhou, China

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

158

Lastpage

162

Abstract

Personal objects in Netnews oral reviews are important component of public opinion. Recognition of personal objects is the base of sentiment analysis for oral reviews. This paper analyzes the characteristics of personal objects in Netnews oral reviews. Based on these characteristics, we present an efficient recognition approach. The approach firstly evaluates reliability of one Chinese character as part of personal object to get reliable and discriminating recognition clues; Secondly, through an improved algorithm of frequent pattern mining, we obtain candidate objects from processing windows using the clues; Lastly, make use of a series of rules to optimize the results. The experimental results show the approach can integrally and efficiently identify personal objects in Netnews oral reviews.

Keywords

character recognition; data mining; information resources; Chinese character; Netnews oral reviews; efficient recognition approach; frequent pattern mining; personal objects recognition; public opinion; sentiment analysis; Communication system control; Control systems; Cost function; Educational institutions; Electronic mail; Force control; Information systems; Nonlinear control systems; Subcontracting; Support vector machines; Netnews oral reviews; frequent pattern mining; personal objects; public opinion;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Information Systems and Mining, 2009. WISM 2009. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3817-4

Type

conf

DOI

10.1109/WISM.2009.40

Filename

5368979