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  1. University of Information Technology
  2. International Conference on Advanced Information Technologies

Feature Extraction Method for Aspect-Based Sentiment Analysis

https://meral.edu.mm/records/6638
https://meral.edu.mm/records/6638
4907bc88-4170-46ce-bc44-1f2c1dd41a9e
fc8b9e02-fe75-4e60-a501-3e9e0963deff
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Feature Feature Extraction Method for Aspect-Based Sentiment Analysis.pdf (375 Kb)
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Publication type
Conference paper
Upload type
Publication
Title
Title Feature Extraction Method for Aspect-Based Sentiment Analysis
Language en
Publication date 2017-11-02
Authors
Win Lei Kay Khine
Nyein Thwet Thwet Aung
Thet Thet Zin
Description
In our daily life, we take opinions of our friends and we
are influenced in decision making process. Opinion is
the view or the judgment about something. Opinion
Mining (OM) or Sentiment Analysis (SA) is the
computational analysis of public’s opinion, emotion,
sentiments, and attitude toward entities and their
attributes expressed in written text. These entities may
be products, services, organizations, individuals, events,
issues, or topics. In sentiment analysis, formal and
informal opinion text like product reviews, news
articles, tweets, forum discussions, blogs, and Facebook
posts are also applicable to all domains. The main
purpose of sentiment analysis is to extract the main
opinions, on which the decision can be made very right.
Paper intends to classify sentiment polarity on product
review datasets by using Mutual Information as a
feature selection method. Because product reviews are
highly focused and they are opinion rich. After the
feature selection, we aim to classify the extracted
features with Naïve Bayes, SVM and Maximum Entropy
to get the accurate sentiment polarity.
Keywords
Sentiment Analysis, Opinion Mining, Feature Selection, Feature Extraction, Aspect-Based Sentiment Analysis
Conference papers
ICAIT-2017
1-2 November, 2017
1st International Conference on Advanced Information Technologies
Yangon, Myanmar
Workshop Session
https://www.uit.edu.mm/icait-2017/
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