On the Integration of Deep Learning and Fuzzy Methods for Aspect-based Sentiment Analysis

Yu Chieh Wu, Jie Chi Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Sentiment analysis is an important task in the field of big data and artificial intelligence and has a wide range of real-world applications. The majority of current approaches, however, attempt to detect the overall polarity of a sentence, or text span, irrespective of the entities mentioned and their aspects. A typical way for solve this is to employ a classifier that learns to identify the polarity labels given input text. Such methods require amount of training examples which were manually constructed. While most work in text mining in the field of sentiment analysis domain focus on the use of supervised machine learning technologies, in this paper, we investigate on aspect-based sentiment analysis for mobile game reviews. Our method integrates both deep learning learned features and support vector machines. The deep learning feature is mainly derived from inducting word relations in Wikipedia and the collected in-domain text. To prevent from assessing unknown missing words, we design a fuzzy-based approach to capture word-level sentiment scores. By using a fuzzy-based soft computing strategy with a small lexicon allows us to produce a system with better accuracy and precision than pure machine learning such as Naïve Bayes and SVMs. To demonstrate the effectiveness of the proposed approach, we conduct the experimental results on the collected Mobile game reviews. These results show that our method outperforms supervised systems. One good property of this method is that it does not need to perform Chinese word segmentation in testing time.

Original languageEnglish
Title of host publicationProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages483-488
Number of pages6
ISBN (Electronic)9781728126272
DOIs
StatePublished - Jul 2019
Event8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019 - Toyama, Japan
Duration: 7 Jul 201911 Jul 2019

Publication series

NameProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019

Conference

Conference8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019
Country/TerritoryJapan
CityToyama
Period7/07/1911/07/19

Keywords

  • deep learning
  • natural language processing
  • sentiment analysis
  • text mining

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