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作 者:PAN Ding SHEN Jun-yi ZHOU Mu-xin
机构地区:[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
出 处:《Wuhan University Journal of Natural Sciences》2006年第1期165-169,共5页武汉大学学报(自然科学英文版)
基 金:Supported by the National Natural Science Foun-dation of China (60173058 ,70372024)
摘 要: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.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.
关 键 词:continuous data mining domain knowledge ONTOLOGY FRAMEWORK
分 类 号:TP311.13[自动化与计算机技术—计算机软件与理论]
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