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KDD
1997
ACM
104views Data Mining» more  KDD 1997»
13 years 11 months ago
An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases
Efficient discover of association rules in large databases is a we 1 studied problem and several ap-1y proaches have been proposed. However, it is non trivial to maintain the asso...
Shiby Thomas, Sreenath Bodagala, Khaled Alsabti, S...
KDD
1997
ACM
104views Data Mining» more  KDD 1997»
13 years 11 months ago
Proposal and Empirical Comparison of a Parallelizable Distance-Based Discretization Method
Many classification algorithms are designed to work with datasets that contain only discrete attributes. Discretization is the process of converting the continuous attributes of ...
Jesús Cerquides, Ramon López de M&aa...
KDD
1997
ACM
114views Data Mining» more  KDD 1997»
13 years 11 months ago
Schema Discovery for Semistructured Data
To formulate a meaningful query on semistructured data, such as on the Web, that matches some of the source’s structure, we need first to discover something about how the infor...
Ke Wang, Huiqing Liu
KDD
1997
ACM
109views Data Mining» more  KDD 1997»
13 years 11 months ago
A Dataset Decomposition Approach to Data Mining and Machine Discovery
We present a novel data mining approach based on decomposition. In order to analyze a given dataset, the method decomposes it to a hierarchy of smaller and less complex datasets t...
Blaz Zupan, Marko Bohanec, Ivan Bratko, Bojan Cest...
KDD
1997
ACM
92views Data Mining» more  KDD 1997»
13 years 11 months ago
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation
This paper describes how to increase the efficiency of inductive data mining algorithms by replacing the central matching operation with a marker propagation technique. Breadth-fi...
John M. Aronis, Foster J. Provost