基于先验的教学评价方法

Jiabin Deng, Juanli Hu, He-hua Chi, Juebo Wu
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引用次数: 3

摘要

智能评估是模拟领域专家解决复杂问题的决策过程,是人工智能领域的一个重要分支。本文提出了一种基于改进Apriori的智能评价方法,可用于挖掘不同层次的关联规则,自动评价教学质量。首先,针对传统Apriori算法的不足,对其进行改进。其次,描述了基于该改进算法的教学质量评价过程。最后给出了一个算例,结果表明了该方法的可行性和有效性。
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An Apriori-Based Approach for Teaching Evaluation
Intelligent evaluation, as an important branch in the field of artificial intelligence, is a decision-making process of simulating the domain experts to solve complex problems. In this paper, we puts forward a kind of intelligent evaluation method based on improved Apriori, which can be used to mine different levels of association rules and evaluate the teaching quality automatically. Firstly, we do some improvement on traditional Apriori algorithm due to its shortcomings. Secondly, we describe the procedure of the teaching quality evaluation based on such improved algorithm. Finally, we give an example and the results show that this method is feasible and effective.
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