MCQA: A Responsive Question-answering System for Online Education

被引：0
作者：
Wang, Yi [1 ]
Deng, Jinsheng [1 ]
Yang, Xi [1 ]
Yi, Jianyu [2 ]
Ye, Zhaohui [1 ]
机构：
[1] Natl Univ Def Technol, 109 Deya Rd, Changsha 410073, Peoples R China
[2] Fudan Univ, 220 Handan Rd, Shanghai 200433, Peoples R China
来源：
SENSORS AND MATERIALS | 2023年 / 35卷 / 12期
关键词：
QA system; MOOCs; question classification; similarity retrieval; similarity computation; chitchat generation; CLASSIFICATION;
D O I：
10.18494/SAM4483
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
Massive Open Online Courses (MOOCs) are now considered as representatives of online education. In addition to watching course videos and taking tests, online question & answering (Q&A) also plays an important role during MOOC learning. In this paper, we introduce a question-answering (QA) system called MCQA for MOOCs. The system comprises several modules, including question classification, similarity retrieval, similarity computation, and chitchat generation. On a real MOOC platform, MCQA demonstrates exceptional performance, with experimental results showing a precision rate exceeding 90% and an average duration of a Q&A session of less than 100 ms. Compared with other Chinese-based QA systems, MCQA provides superior open-ended QA capabilities, excelling in performance and covering numerous learning scenarios.
引用
收藏
页码：4325 / 4336
页数：12
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