A rule-based, domain independent approach for opinion and holder identification

Author

Sima, Ioana Maria ; Vunvulea, Mariana

Author_Institution

Dept. of Comput. Sci., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania

fYear

2013

fDate

5-7 Sept. 2013

Firstpage

55

Lastpage

62

Abstract

Mining sentiments from text is currently an important problem in information retrieval systems. In this paper we propose a solution for extracting opinions and opinion holders from large texts. Our goal is to achieve a high level of domain independence by implementing a rule-based approach. The results of our system have proven an accuracy which is comparable to that of systems that use a supervised learning approach, which is domain dependent.

Keywords

data mining; information retrieval; learning (artificial intelligence); text analysis; holder identification; information retrieval systems; large texts; opinion identification; rule-based domain independent approach; supervised learning approach; text mining; Computer science; Context; Educational institutions; Information retrieval; Semantics; Speech; Supervised learning; domain independence; opinion; opinion holder; opinion target; sentiment polarity;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computer Communication and Processing (ICCP), 2013 IEEE International Conference on

Conference_Location

Cluj-Napoca

Print_ISBN

978-1-4799-1493-7

Type

conf

DOI

10.1109/ICCP.2013.6646081

Filename

6646081