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» Methods for finding frequent items in data streams
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BMCBI
2006
126views more  BMCBI 2006»
13 years 7 months ago
Effect of data normalization on fuzzy clustering of DNA microarray data
Background: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is informati...
Seo Young Kim, Jae Won Lee, Jong Sung Bae
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 9 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin
ICDE
2007
IEEE
123views Database» more  ICDE 2007»
14 years 9 months ago
Stream Monitoring under the Time Warping Distance
The goal of this paper is to monitor numerical streams, and to find subsequences that are similar to a given query sequence, under the DTW (Dynamic Time Warping) distance. Applica...
Yasushi Sakurai, Christos Faloutsos, Masashi Yamam...
ICDM
2006
IEEE
132views Data Mining» more  ICDM 2006»
14 years 1 months ago
High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Hassan H. Malik, John R. Kender
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 8 months ago
Cleaning disguised missing data: a heuristic approach
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially va...
Ming Hua, Jian Pei