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» Clustering Rules Using Empirical Similarity of Support Sets
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ISMIR
2005
Springer
206views Music» more  ISMIR 2005»
15 years 3 months ago
Improving Content-Based Similarity Measures by Training a Collaborative Model
We observed that for multimedia data – especially music - collaborative similarity measures perform much better than similarity measures derived from content-based sound feature...
Richard Stenzel, Thomas Kamps
DEXA
2008
Springer
123views Database» more  DEXA 2008»
14 years 11 months ago
Emerging Pattern Based Classification in Relational Data Mining
The usage of descriptive data mining methods for predictive purposes is a recent trend in data mining research. It is well motivated by the understandability of learned models, the...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
BMCBI
2008
142views more  BMCBI 2008»
14 years 9 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
WSDM
2010
ACM
204views Data Mining» more  WSDM 2010»
15 years 4 months ago
Learning URL patterns for webpage de-duplication
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we pres...
Hema Swetha Koppula, Krishna P. Leela, Amit Agarwa...
SPAA
2003
ACM
15 years 2 months ago
A proportionate fair scheduling rule with good worst-case performance
In this paper we consider the following scenario. A set of n jobs with different threads is being run concurrently. Each job has an associated weight, which gives the proportion ...
Micah Adler, Petra Berenbrink, Tom Friedetzky, Les...