计算机科学
主动学习(机器学习)
平面图(考古学)
互联网
人工智能
机器学习
主动学习
机器人学习
万维网
移动机器人
机器人
历史
考古
作者
Xinying Hu,Yu He,Guangzhong Sun
标识
DOI:10.1145/3457682.3457771
摘要
The prerequisite relationship of the concept plays an important role in education. Previously, the prerequisites were given by experts, which is very costly. With the development of the Internet, many new concepts have emerged. And there are a growing number of electronic materials available. In this case, it's important to produce an efficient and accessible prerequisite annotator that is beneficial to make an efficient learning plan. This paper proposes a method to mine prerequisite relationships of concepts from Wikipedia by using active learning, which can use fewer artificial labels to obtain an accurate model. The proposed method extracts features from Wikipedia articles, and designs a new active learning algorithm based on the characteristics of concept prerequisites. Experimental results show that the proposed model outperforms existing active learning methods for concept prerequisite learning.
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