JDCTA
2010
12 years 12 months ago
2010
High-dimensional mixed-attribute data clustering has become an important research direction in data mining area. Because of the advantages of the information technology, data coll...
ICC
2009
IEEE
13 years 2 months ago
2009
IEEE
In this paper, Internet data collected via passive measurement are analyzed to obtain localization information on nodes by clustering (i.e., grouping together) nodes that exhibit s...
SAC
2008
ACM
13 years 4 months ago
2008
ACM
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
SIGMOD
1998
ACM
13 years 9 months ago
1998
ACM
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
PAKDD
2004
ACM
13 years 10 months ago
2004
ACM
Abstract. Traditional clustering algorithms are based on one representation space, usually a vector space. However, in a variety of modern applications, multiple representations ex...
GRC
2005
IEEE
13 years 10 months ago
2005
IEEE
Abstract. A new methodology that structures the semantics of a collection of documents into the geometry of a simplicial complex is developed. A simplicial complex is topologically...
ADBIS
2007
Springer
2007
Springer
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA
13 years 11 months ago
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...
FSKD
2009
Springer
13 years 11 months ago
2009
Springer
Usually a meaningful web topic has tens of thousands of comments, especially the hot topics. It is valuable if we congregate the comments into clusters and find out the mainstrea...
SDM
2009
SIAM
14 years 2 months ago
2009
SIAM
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
SDM
2009
SIAM
14 years 2 months ago
2009
SIAM
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...