QUESTION ANSWERING SYSTEM IN FITNESS DOMAIN BASED ON MACHINE LEARNING
DOI:
https://doi.org/10.24867/16BE05KaticKeywords:
Chatbot, Language models, NLP, QA, BERTAbstract
This paper presents system for question answering focused on fitness and nutrition field, that works just as well in open domain. As an input model accepts a question in a form of array of characters and finds best document candidates in a knowledge base from which the actual answer is extracted.
References
[1] Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
[2] Lewis, P., Denoyer, L., Riedel, S. (2019). Unsupervised Question Answering by Cloze Translation. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
[3] Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, Ming Zhou. (2020). MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers.
[4] Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, & Veselin Stoyanov. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach
[5] Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih. (2020). Dense Passage Retrieval for Open-Domain Question Answering.
[6] Yang, Zhilin, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. "Xlnet: Generalized autoregressive pretraining for language understanding." arXiv preprint arXiv:1906.08237 (2019).
[7] Victor Sanh, Lysandre Debut, Julien Chaumond, & Thomas Wolf. (2020). DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.
[8] Sina J. Semnani, & Manish Pandey. (2020). Revisiting the Open-Domain Question Answering Pipeline.
[2] Lewis, P., Denoyer, L., Riedel, S. (2019). Unsupervised Question Answering by Cloze Translation. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
[3] Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, Ming Zhou. (2020). MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers.
[4] Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, & Veselin Stoyanov. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach
[5] Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih. (2020). Dense Passage Retrieval for Open-Domain Question Answering.
[6] Yang, Zhilin, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. "Xlnet: Generalized autoregressive pretraining for language understanding." arXiv preprint arXiv:1906.08237 (2019).
[7] Victor Sanh, Lysandre Debut, Julien Chaumond, & Thomas Wolf. (2020). DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.
[8] Sina J. Semnani, & Manish Pandey. (2020). Revisiting the Open-Domain Question Answering Pipeline.
Downloads
Published
2022-01-26
Issue
Section
Electrotechnical and Computer Engineering
