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Incorporating Domain Knowledge into Data Mining Process: An Ontology Based Framework
作者姓名:PAN  Ding  SHEN  Jun-yi  ZHOU  Mu-xin
作者单位:[1]Department of Computer Science and Technology,Xi'an jiaotong University, Xi'an 710049, Shaanxi, China [2]Department of Computer Science and Engineering,Shanghai Jiaotong University, Shanghai 200240, China
基金项目:Supported by the National Natural Science Foun dation of China (60173058, 70372024)
摘    要:0 IntroductionTeosda,yth meyan hya voerg daantiazbaatisoenss t hhaatv ec hmaonrgee t ahnadn glarrogwe cdoatnatibnaus--ously. One of the i mportant research issues is incrementalmining. Otherwise, various researchers have made sugges-tions that domain knowledge should be incorporated intoknowledge discovery ( KDD) process1]. We focus on somesteps of the KDDprocess-those steps tying up with data min-ing,called a data mining (DM) process .Agrawalet al2]showed an active data mining process ,…

关 键 词:连续数据挖掘  领域知识  数据库  存在论  数据结构
文章编号:1007-1202(2006)01-0165-05
收稿时间:2005-04-10

Incorporating domain knowledge into data mining process: An ontology based framework
PAN Ding SHEN Jun-yi ZHOU Mu-xin.Incorporating domain knowledge into data mining process: An ontology based framework[J].Wuhan University Journal of Natural Sciences,2006,11(1):165-169.
Authors:Pan Ding  Shen Jun-yi  Zhou Mu-xin
Institution:(1) Department of Computer Science and Technology, Xi'an Jiaotong University, 710049 Xi'an Shaanxi, China;(2) Department of Computer Science and Engineering, Shanghai Jiaotong University, 200240 Shanghai, China
Abstract:With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.
Keywords:continuous data mining  domain knowledge  ontology  framework
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