JSAI2020

Presentation information

General Session

General Session » J-9 Natural language processing, information retrieval

[4Q2-GS-9] Natural language processing, information retrieval: Q&A system

Fri. Jun 12, 2020 12:00 PM - 1:40 PM Room Q (jsai2020online-17)

座長:吉野幸一郎(NAIST)

1:20 PM - 1:40 PM

[4Q2-GS-9-05] Collecting Chinese Know-How Question Answering Examples and Application of Neural Machine Comprehension Model

〇Tengyang Chen1, Zechang Qian2, Hongyu Li1, Takehito Utsuro1, Yasuhide Kawada3 (1. University of Tsukuba, 2. Tokyo University of Technology, 3. Logworks Co., Ltd.)

Keywords:question answering, machine comprehension, tip, BERT, Chinese

In the recent research, the state-of-the-art technique has achieved much gain in the field of question answering,
and the result is comparable to the human-being’s. On the contrary, there are limited research focusing on the field
of non-factoid question answering. This thesis studies how to develop a dataset for training Chinese tip question
answering models. In this thesis, then the Chinese tip questions and answers dataset is used to train one of
the state-of-the-art machine comprehension models. This thesis also compares the trained tip question answering
model to a Chinese factoid question answering model which is trained with a Chinese factoid questions and answers
dataset. Evaluation result shows that the model trained with the mixture of tip and factoid question and answers
datasets achieve the best performance.

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