data mining造句
91. Active incremental data mining is implemented by applying the trigger mechanism of the database to invoke procedures.
92. Secondly, this thesis studies the email data mining technology especially the email classification method.
93. Its about the analysis of data mining application under educational information condition, hope to offer value.
94. In this paper, a intelligent analysis mode based on Data Mining in Armored Equipment Maintenance and Management is presented to get a useful knowledge for the decisionmaker.
95. Using a relatively common algorithm CRD method as its basis, the kit can be divided into three main models which are data preprocessing, data mining and data evaluation.
96. Temporal data mining has the capability to discover patterns or rules which might be overlooked when the temporal component is ignored or treated as a simple numeric attribute.
97. In the previous two articles in this " Data mining with WEKA" series, I introduced the concept of data mining.
98. High - dimensional data mining faces the challenges of distributed data sparsity and overlapping feature subspace.
99. We study the incremental data mining technology based outlier factor.
100. After discussing the control field format of microcommand in computer execution unit, an efficient algorithm is put forth. Then this algorithm is optimized through the search strategy of data mining.
101. It is thought that the data mining is the multistage process of user' s center in this thesis.
102. The spatial clustering analysis is a method of the spatial data mining. The spatial clustering analysis can directly find some useful clustering structure from spatial database.
103. Clustering analysis is important part of data mining. It is an unsupervised learning process and it doesn't need prior knowledge about data set.
104. This paper builds a Bayesian inference network model based on the Rough Sets and Reason Rules and apply it to fulfill the medical data mining work.
105. This article wraps up the three-article series introducing you to the concepts of data mining and especially to the WEKA software.
106. All in all, a great gulf fixed request to exploit the tools of data mining, and convert the data " grave" to knowledge "gold ".
107. Now, Rough Set theory is becoming a new hotspot of artificial intelligence domain. More and more scholar focuse on the incremental data mining technology based on rough set theory.
108. However, the datasets which data mining search always contain missing data.
109. This paper also studies the method of marketing management decision-making model by data mining technique.
110. And then, an approach for knowledge reduction is given in the construction of history knowledge base to store interesting rules in incremental data mining.
111. Data -reduction-based approximate data mining technique in which data reduction for massive data set was done in data pretreatment phase has been discussed.
112. To mine the association rules with multi dimensional numeric attribute is a difficult problem in data mining area.
113. It has been developed with the objective of serving as an annotated and curated database comprising complete genome sequences of viruses, value-added derived data and data mining tools.
114. There are two types of data mining methods integration, they are horizontal integration and vertical integration.
115. The paper briefly introduces the concept of privacy preserving data mining technology and studies the application of decision tree classifier in this particular field.
116. Spatial Data Mining is a research branch of data mining, and the spatial clustering analysis is an important area of research of spatial data mining.
117. Our proposed CAAR algorithm is applied to supervised classification of image content and large-scale data mining, which is very effective.
118. Depending on all above studies and experiments, we can conclude that using data mining distill prosodic rules in speech synthesis is viable.
119. Through actual validating, the results indicate that this application used in telecom system based on data mining is more effective.
120. Clustering analysis is one of the important data mining techniques that can discover hidden modes by unsupervised learning and has the ability of acquiring knowledge independently.
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