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The Research of Mining Association Rules Between Personality and Behavior of Learner Under Web-Based Learning Environment

机译:基于Web的学习环境下人格与学习者人格与行为的矿业与行为的研究

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Discovering the relationship between behavior and personality of learner in the web-based learning environment is a key to guide learners in the learning process. This paper proposes a new concept called personality mining to find the "deep" personality through the observed data about the behavior. First, a learner model which includes personality model and behavior model is proposed. Second, we have designed and implemented an improved algorithm, which is based on Apriori algorithm widely used in market basket analysis, to identify the relationship. Third, we have discussed various issues like constructing the learner model, unifying the value domain of heterogeneous model attributes, and improving Apriori algorithm with decision domain. Experiment result indicated that this algorithm for mining association rules between behavior and personality is feasible and efficient. The algorithm has been used in a web-based learning environment developed at Xi'an Jiaotong University.
机译:在基于Web的学习环境中发现学习者行为和人格之间的关系是指导学习过程中的学习者的关键。本文提出了一种名为人格挖掘的新概念,通过观察到的行为的数据来找到“深度”个性。首先,提出了包括个性模型和行为模型的学习者模型。其次,我们已经设计和实施了一种改进的算法,其基于广泛用于市场篮子分析的APRiori算法,以识别关系。第三,我们已经讨论了构建学习者模型的各种问题,统一异构模型属性的价值域,以及用决策域改进APRIORI算法。实验结果表明,该算法在行为和人格之间采矿协会规则是可行和有效的。该算法已在西安交通大学开发的基于网络的学习环境中使用。

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