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» CURE: An Efficient Clustering Algorithm for Large Databases
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135
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ICDE
2007
IEEE
129views Database» more  ICDE 2007»
15 years 9 months ago
Ontology-driven Rule Generalization and Categorization for Market Data
—Radio Frequency Identification (RFID) is an emerging technique that can significantly enhance supply chain processes and deliver customer service improvements. RFID provides use...
Dongwoo Won, Dennis McLeod
143
Voted
CIKM
2009
Springer
15 years 1 months ago
Diverging patterns: discovering significant frequency change dissimilarities in large databases
In this paper, we present a framework for mining diverging patterns, a new type of contrast patterns whose frequency changes significantly differently in two data sets, e.g., it c...
Aijun An, Qian Wan, Jiashu Zhao, Xiangji Huang
152
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IDEAS
2006
IEEE
218views Database» more  IDEAS 2006»
15 years 9 months ago
PBIRCH: A Scalable Parallel Clustering algorithm for Incremental Data
We present a parallel version of BIRCH with the objective of enhancing the scalability without compromising on the quality of clustering. The incoming data is distributed in a cyc...
Ashwani Garg, Ashish Mangla, Neelima Gupta, Vasudh...
KDD
2006
ACM
142views Data Mining» more  KDD 2006»
16 years 3 months ago
Mining distance-based outliers from large databases in any metric space
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
Yufei Tao, Xiaokui Xiao, Shuigeng Zhou
ISMB
1998
15 years 4 months ago
Automated Clustering and Assembly of Large EST Collections
The avMlability of large EST(Expressed Sequence Tag)databases has led to a revolution in the waynew genes are cloned. Difficulties arise, however,due to high error rates and redun...
David P. Yee, Darrell Conklin