By Topic

Chinese Sentence-Level Sentiment Classification Based on Sentiment Morphemes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xin Wang ; Sch. of Comput. Sci. & Technol., Heilongjiang Univ., Harbin, China ; Guohong Fu

In this paper, we take morphemes as the basic tokens and present a fine-to-coarse strategy for Chinese sentence-level sentiment classification. This study involves three parts. First, we employ morphological productivity to extract sentiment morphemes from a sentiment dictionary and to calculate their polarity intensity at the same time. Then, we apply the acquired morpheme-level sentiment information to predict the semantic orientation of sentiment words and phrases within an opinionated sentence. Finally, all the sentiment phrases and their polarity scores are combined to determine the semantic orientation of the sentence. The experimental results on NTCIR-6 OAPT test set show our system can achieve state-of-the-art performance.

Published in:

Asian Language Processing (IALP), 2010 International Conference on

Date of Conference:

28-30 Dec. 2010