Titlebook: Knowledge Discovery and Data Mining. Current Issues and New Applications; Current Issues and N Takao Terano,Huan Liu,Arbee L. P. Chen Confe

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Minimum Message Length Criterion for Second-Order Polynomial Model Discovery The method is compared with a number of other selection criteria in the ability to, in an automated manner, discover a model given the generated data. Of particular interest is the ability of the methods to discover (1) second-order independent variables, (2) independent variables with weak causal

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Frequent Itemset Counting Across Multiple Tablestensions to mining algorithms for decentralized data have largely been for load balancing. In this paper, we examine mining decentralized data for the task of finding frequent itemsets. In contrast to current techniques where data is first joined to form a single table, we exploit the inter-table fo

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卡死偷電

An Optimization Problem in Data Cube System Designich is related to the number of cubes materialized, some cubes can be merged, but the resulting larger cubes will increase the response time of answering some queries. In order to satisfy the maintenance bound and response time bound given by the user, we may have to sacrifice some of the queries an

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Exception Rule Mining with a Relative Interestingness Measuresense rule and reference rule. Mining interesting rules is one of the important data mining tasks. Interesting rules bring novel knowledge that helps decision makers for advantageous actions. It is true that interestingness is a relative issue that depends on the other prior knowledge. However, this

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A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databasendexing algorithm that is more than an order of magnitude faster than the previous best known method. In addition to being much faster our approach has numerous other advantages. It is simple to understand and implement, allows more flexible distance measures including weighted Euclidean queries and

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On Association, Similarity and Dependency of Attributescate the closeness of attributes reflected by their values on a set of objects. Two attributes are similar if every object is likely to have the same value on them. Data and functional dependencies show the connection and association between attributes. They are characterized by the problem of deter