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» A data mining approach to database compression
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KDD
2010
ACM
279views Data Mining» more  KDD 2010»
15 years 7 months ago
Unifying dependent clustering and disparate clustering for non-homogeneous data
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
KDD
1998
ACM
145views Data Mining» more  KDD 1998»
15 years 8 months ago
Aggregation of Imprecise and Uncertain Information for Knowledge Discovery in Databases
We consider the problem of aggregation for uncertain and imprecise data. For such data, we define aggregation operators and use them to provide information on properties and patte...
Sally I. McClean, Bryan W. Scotney, Mary Shapcott
120
Voted
KDD
2006
ACM
150views Data Mining» more  KDD 2006»
16 years 4 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
KES
2005
Springer
15 years 9 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
142
Voted
ADBIS
2007
Springer
132views Database» more  ADBIS 2007»
15 years 10 months ago
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Rayner Alfred, Dimitar Kazakov