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Joining Aspect Detection and Opinion Target Expression Based on Multi-Deep Learning Models

In: Applications in Reliability and Statistical Computing

Author

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  • Bui Thanh Hung

    (Industrial University of Ho Chi Minh City)

Abstract

Aspect-based Sentiment Analysis (ABSA) is an advanced task as well as technique which is developed based on sentiment analysis. Aspect-based sentiment analysis is a text analysis technique that categorizes data by aspect and identifies the sentiment attributed to each one. Aspect-based sentiment analysis can be used to analyze customer feedback data by associating specific sentiments with different aspects (e.g. the attributes or components) of a product or service. This has attracted increasing attention in the recent few years in Natural Language Processing and has broad applications in both research and business. In this research, we apply joining aspect detection and opinion target expression using multi-deep learning methods: RNN, LSTM and CNN and we do experiments on Vietnamese VLSP2018 dataset. Both of the results for the aspect detection as well as opinion target expression achieve the best results on the CNN model.

Suggested Citation

  • Bui Thanh Hung, 2023. "Joining Aspect Detection and Opinion Target Expression Based on Multi-Deep Learning Models," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Applications in Reliability and Statistical Computing, pages 85-96, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-21232-1_4
    DOI: 10.1007/978-3-031-21232-1_4
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