已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Intelligent Question and Answer System Based on Course Knowledge Graph

计算机科学 知识图 知识空间 答疑 图形 构造(python库) 知识工程 基于知识的系统 知识管理 人工智能 理论计算机科学 程序设计语言
作者
Pengyuan Shi,Yunxia Fan,Zichao Zhuang,Mingwen Tong
标识
DOI:10.1109/cste59648.2023.00035
摘要

With the development of time, online education such as catechism is widely used, and it is difficult to meet the personalized learning needs of learners because of the difficulty of timely communication between teachers and students while breaking space and time. The intelligent question and answer system integrating subject knowledge can meet learners' knowledge retrieval and personalized learning and make up for teachers' lack of energy. Currently, intelligent question and answer systems based on knowledge graph are receiving attention from researchers in the education field, however, Chinese knowledge graphs for university courses and intelligent question and answer systems based on them are lacking. To address this problem, we propose to construct a Chinese course knowledge graph and design and implement an intelligent question and answer system based on the course knowledge graph. The main contributions of this paper are as follows. Firstly, we designed and implemented an intelligent question and answer system based on the method of building templates. Then, we have classified the knowledge of the Introduction to Database Systems course, clarified the attributes and relationships of the knowledge points, and constructed the course knowledge graph. Finally, an external evaluation method was used to collect 30 questions asked by undergraduate students for systematic testing, resulting in 80% satisfaction. The experiment results indicate that the system can answer user questions more accurately and help learners improve the efficiency of independent learning, while giving practical support to the development of knowledge graph intelligent question and answer applications in education.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
2秒前
科研通AI6.4的应助被pcs采纳,获得10
2秒前
Suliove完成签到,获得积分10
2秒前
自然的茉莉完成签到,获得积分10
3秒前
3秒前
小蘑菇的应助被小圭采纳,获得10
4秒前
cccs完成签到,获得积分20
5秒前
包容明辉发布了新的文献求助10
5秒前
Jason发布了新的文献求助10
6秒前
7秒前
在水一方的应助被dq采纳,获得10
7秒前
李爱国的应助被鲜于灵竹采纳,获得10
7秒前
8秒前
8秒前
8秒前
8秒前
11秒前
CodeCraft的应助被高雪采纳,获得10
12秒前
幽默的羿发布了新的文献求助10
13秒前
小白发布了新的文献求助10
14秒前
曾鑫发布了新的文献求助10
14秒前
科研小趴菜完成签到 ,获得积分10
15秒前
jjzz完成签到,获得积分20
16秒前
盐西发布了新的文献求助20
16秒前
16秒前
corn完成签到 ,获得积分10
17秒前
jjzz发布了新的文献求助20
18秒前
19秒前
深情安青的应助被无师自通采纳,获得10
19秒前
pass完成签到 ,获得积分10
19秒前
21秒前
Leo发布了新的文献求助10
21秒前
Qu完成签到 ,获得积分10
22秒前
山野的雾完成签到 ,获得积分10
23秒前
24秒前
会飞的猪发布了新的文献求助10
26秒前
研值爆表完成签到 ,获得积分10
27秒前
Echo完成签到,获得积分10
27秒前
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Organizational Behavior 510
Management and the Arts 510
Issues in Task-Based Language Teaching 500
Geschichtliche Grundbegriffe (GGB), Band 5: Pro–Soz 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7788234
求助须知:如何正确求助?哪些是违规求助? 9326542
关于积分的说明 20411283
捐赠科研通 7377224
什么是DOI,文献DOI怎么找? 3322389
关于科研通互助平台的介绍 2470145
邀请新用户注册赠送积分活动 2339085