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    认知物理学在数据挖掘中的应用研究

    Application Research of Cognitive Physics in Data Mining

    • 摘要: 认知物理学从自然语言切入,研究定量到定性、从数据到知识的思维过程以及思维所运用的信息的形式化组织.借鉴认知物理学的相关理论来研究数据挖掘:首先,借鉴场来研究数据挖掘中复杂知识的表示,提出了语言场这一新的复杂类型知识表示方式;其次,借鉴信息扩散原理来研究参数演化规律中参数波动的情况,从而为数据挖掘的后处理研究提供了新的途径;再次,研究了决策树构造的信息熵方法,提出了认识熵的概念,基于这些概念和方法给出了SID\-3算法,并利用实例说明了SID\-3算法的优越性.

       

      Abstract: Cognitive physics, from the perspective of natural language, focuses on the thinking process that is from quantity to quality and from data to knowledge as well as the organization of information. In this paper, data mining techniques are explored by using cognitive physics theory and its relevant theory. Firstly, by using the theory of field, the language field is illustrated, which is a method for representing complex knowledge. Secondly, by learning from the information spreading theory, the parameter evolution is discussed, which is an important issue for post-processing of data mining. Finally, by analyzing the information entropy method for decision tree construction, the subjective entropy and the corresponding SID\-3 algorithm are proposed. The advantage of the proposed algorithm is illustrated by using an example.

       

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