挖掘所关注规则的多策略方法研究

通过数据挖掘，从大型数据库中发现了大量规则，如何选取所关注的规则，是知识发现的重要研究内容。该文研究了利用领域知识对规则的主观关注程度进行度量的方法，给出了一个能够度量规则的简洁性和新奇性的客观关注程度的计算函数，提出了选取用户关注的规则的多策略方法。

Multi-Strategy Approach to Mining Interesting Rules

A large set of rules can be discovered from large database by using the data mining technologies, but most of them are of no interesting to the user. How to filter the interesting rules is the crucial step within the knowledge discovery in database. The methods to calculate the subjective interestingness and to measure the importance of rules by using of the domain knowledge are studied. A new objective interestingness function, which can measure the novelty and simplicity of rules, is given. A multi strategy approach, which combines with background knowledge, for selecting interesting rules is proposed in the paper. The process of filtering interesting rules includes the several sub processes: deleting the redundant rules; grouping the rules into sub groups; clustering each sub group into classes, and selecting the most interesting rule from each class; finally combining them into the set of interesting rules. Some concepts, such as the importance of attribute, the interestingness of rules, the distance between rules etc, are proposed in the paper. There is an example in the paper, which applying the multi strategy approach, for illustrating the process to select the interesting rules that discovered from CPICDB (chinese parasite infection census database). The example demonstrated the algorithm represented in the paper is practicable and effective.