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» On Finding Similar Items in a Stream of Transactions
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ICDM
2010
IEEE
164views Data Mining» more  ICDM 2010»
13 years 5 months ago
On Finding Similar Items in a Stream of Transactions
While there has been a lot of work on finding frequent itemsets in transaction data streams, none of these solve the problem of finding similar pairs according to standard similar...
Andrea Campagna, Rasmus Pagh
ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
14 years 2 months ago
Finding Associations and Computing Similarity via Biased Pair Sampling
Sampling-based methods have previously been proposed for the problem of finding interesting associations in data, even for low-support items. While these methods do not guarantee ...
Andrea Campagna, Rasmus Pagh
ICDE
2009
IEEE
171views Database» more  ICDE 2009»
14 years 9 months ago
A Framework for Clustering Massive-Domain Data Streams
In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...
Charu C. Aggarwal
SIGMOD
2004
ACM
144views Database» more  SIGMOD 2004»
14 years 7 months ago
Diamond in the Rough: Finding Hierarchical Heavy Hitters in Multi-Dimensional Data
Data items archived in data warehouses or those that arrive online as streams typically have attributes which take values from multiple hierarchies (e.g., time and geographic loca...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
CIKM
2006
Springer
13 years 9 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu