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PAKDD
2011
ACM
419views Data Mining» more  PAKDD 2011»
14 years 7 months ago
DISC: Data-Intensive Similarity Measure for Categorical Data
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
Aditya Desai, Himanshu Singh, Vikram Pudi
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
16 years 4 months ago
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets
We present a novel algorithm called Clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, Clicks mines subs...
Mohammed Javeed Zaki, Markus Peters, Ira Assent, T...
ICDM
2005
IEEE
157views Data Mining» more  ICDM 2005»
15 years 10 months ago
Blocking Anonymity Threats Raised by Frequent Itemset Mining
In this paper we study when the disclosure of data mining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. The novelty o...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
PAKDD
2005
ACM
161views Data Mining» more  PAKDD 2005»
15 years 10 months ago
Online Algorithms for Mining Inter-stream Associations from Large Sensor Networks
We study the problem of mining frequent value sets from a large sensor network. We discuss how sensor stream data could be represented that facilitates efficient online mining and ...
K. K. Loo, Ivy Tong, Ben Kao
DAWAK
2000
Springer
15 years 8 months ago
Mining Frequent Binary Expressions
In data mining, searching for frequent patterns is a common basic operation. It forms the basis of many interesting decision support processes. In this paper we present a new type ...
Toon Calders, Jan Paredaens