TY  - JOUR
T1  - A Span Matrix-based Answer Candidates Detection Model used 2-Step Learning
AU  - Kim, Boeun 
AU  - Jang, Youngjin 
AU  - Kim, Harksoo 
JO  - Journal of KIISE, JOK
PY  - 2021
DA  - 2021/1/14
DO  - 10.5626/JOK.2021.48.5.539
KW  - answer candidates detection
KW  - question generation
KW  - question-answering
KW  - automatic data construction
KW  - span matrix
KW  - 2-step learning
AB  - Automatic data construction refers to a technology that automatically constructs data through algorithms or deep neural networks. The automated construction system of question-answer data aimed at in this paper was mainly studied through a question generation model, which signifies a model that generates questions related to a given paragraph. Previously, paragraph and answer candidates were entered into the question generation model and related questions were generated. The answer candidates" input to the question generation model was detected through a rule-based method or a method using a deep neural network. We judged that answer detection, which is a subtask of question generation, will have a great influence on question generation. Consequently, we have proposed answer candidates detection model and 2-step learning method using Span Matrix. An experiment was conducted to find out how the questions generated through various methods of extracting answer candidates affect the question-answering system. The proposed model extracted a large number of correct answers compared to the existing model, and the noise in the learning process was supplemented by using the entity name dataset. Apparently, it was confirmed that the question-answer data generated as answer candidates extracted by the proposed model contributed the most to the performance of the question-answer system.