Communism and sign : From linguistic rule to performative shift

2018 ◽  
Vol 57 ◽  
pp. 27-57
Author(s):  
Soo-Hwan Kim
Keyword(s):  
Linguistic Rule

DETECTING EMOTION CAUSES WITH A LINGUISTIC RULE-BASED APPROACH1

2012 ◽  
Vol 29 (3) ◽  
pp. 390-416 ◽  
Author(s):  
Sophia Yat Mei Lee ◽  
Ying Chen ◽  
Chu-Ren Huang ◽  
Shoushan Li
Keyword(s):  
Rule Based ◽  
Linguistic Rule

Aspect Based Sentiment Analysis of Unlabeled Reviews using Linguistic Rule Based LDA

2022 ◽  
Vol 24 (3) ◽  
pp. 0-0
Keyword(s):  
Social Networks ◽  
Sentiment Analysis ◽  
Domain Knowledge ◽  
Latent Dirichlet Allocation ◽  
Rule Based ◽  
Aspect Extraction ◽  
Linguistic Rule ◽  
Digital Era ◽  
Average Accuracy ◽  
Linguistic Rules

In this digital era, people are very keen to share their feedback about any product, services, or current issues on social networks and other platforms. A fine analysis of these feedbacks can give a clear picture of what people think about a particular topic. This work proposed an almost unsupervised Aspect Based Sentiment Analysis approach for textual reviews. Latent Dirichlet Allocation, along with linguistic rules, is used for aspect extraction. Aspects are ranked based on their probability distribution values and then clustered into predefined categories using frequent terms with domain knowledge. SentiWordNet lexicon uses for sentiment scoring and classification. The experiment with two popular datasets shows the superiority of our strategy as compared to existing methods. It shows the 85% average accuracy when tested on manually labeled data.

Three-objective genetics-based machine learning for linguistic rule extraction

2001 ◽  
Vol 136 (1-4) ◽  
pp. 109-133 ◽  
Author(s):  
Hisao Ishibuchi ◽  
Tomoharu Nakashima ◽  
Tadahiko Murata
Keyword(s):  
Machine Learning ◽  
Rule Extraction ◽  
Linguistic Rule
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