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Data mining is to extract the interested information or knowledge from large databases using a series of techniques. The information and knowledge are generally hidden, unknown, but potentially useful, which can be expressed as concepts, rules, laws, modes or other forms. This article introduces the background and concepts of data mining, and reviews its application in medicine and the diagnosis of breast cancer for the most recent years. We also discuss the significance and current problems of this application in the diagnosis of breast cancer.

Cloud mapping relations among variables were learnt by a five layers cloud neural network, then cloud decision trees were extracted from that network. The learning method of neural network and the deducing method of cloud decision tree were presented, the approach combines the learning ability of neural network with the ability of cloud model which deals with the ambiguity of knowledge. The approach makes use of the weights of cloud mappings in the learnt cloud neural network, can realize the optimization of cloud decision trees by branches cutting, and improves the ratio of correctness and efficiency of induction of decision trees. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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The inter-basin water transfer operation belongs to the conventional water transfer planning operation mode, and the real-time information is not considered in the operation. To solve this problem, the decision tree method in data mining is used combining the current reservoir forecast information, underlaying surface water storage condition, perennial reservoir running situation and other data with the reservoir managers' actual operation experiences, and then, the inter-basin water transfer real-time operation rules can be realized. Research process has three steps. Firstly, initial reservoir water level, actual rainfall, GFS forecasting rainfall, soil moisture, diversion water quantity, etc. are selected to compose the reservoir operation data set. Secondly, the inter-basin water transfer operation decision tree is extracted by using data mining technology. Finally, the operation decision tree is tested and the inter-basin water transfer real-time operation rules are obtained. The actual example results show that using decision tree inter-basin water transfer operation rules in the reservoir operating can increase the water resource efficiency and the reservoir comprehensive benefits. This research result has some reference value for the further study and application of the inter-basin water transfer real-time operation. [ABSTRACT FROM AUTHOR]

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