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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 9 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 9 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
CIKM
2006
Springer
14 years 21 days ago
Mining blog stories using community-based and temporal clustering
In recent years, weblogs, or blogs for short, have become an important form of online content. The personal nature of blogs, online interactions between bloggers, and the temporal...
Arun Qamra, Belle L. Tseng, Edward Y. Chang
ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
14 years 3 months ago
Privacy Preserving Nearest Neighbor Search
Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privac...
Mark Shaneck, Yongdae Kim, Vipin Kumar
SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
14 years 6 months ago
Parallel Pairwise Clustering.
Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...
Elad Yom-Tov, Noam Slonim