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All Journal IPTEK The Journal of Engineering
Dimas adi
Department of Computer Science, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Mechanical Engineering

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Explainable Artificial Intelligence (XAI) towards Model Personality in NLP task Dimas adi; Nadhila Nurdin
IPTEK The Journal of Engineering Vol 7, No 1 (2021)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v7i1.a8989

Abstract

In recent years, the development of Deep Learning in the field of Natural Language Processing, especially in sentiment analysis, has achieved significant progress and success. It is because of the availability of large amounts of text data and the ability of deep learning techniques to produce sophisticated predictive results from various data features. However, the sophisticated predictions that are not accompanied by sufficient information on what is happening in the model will be a major setback. Therefore, the significant development of the Deep Learning model must be accompanied by the development of the XAI method, which helps provide information about what drives the model to get predictable results. Simple Bidirectional LSTM and complex Bi-GRU-LSTM-CNN model for Sentiment Analysis were proposed in the present research. Both models were analyzed further using three different XAI methods (LIME, SHAP, and Anchor) in which they were used and compared to two proposed models, proving that XAI is not limited to giving information about what happens in the model but can also help us to understand and distinguish models’ personality and behaviour.
Co-Authors Nadhila Nurdin