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KDD
2005
ACM
103views Data Mining» more  KDD 2005»
15 years 11 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
KDD
2005
ACM
92views Data Mining» more  KDD 2005»
15 years 11 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
KDD
2004
ACM
168views Data Mining» more  KDD 2004»
15 years 11 months ago
Mining, indexing, and querying historical spatiotemporal data
In many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. ...
Nikos Mamoulis, Huiping Cao, George Kollios, Mario...
KDD
2003
ACM
214views Data Mining» more  KDD 2003»
15 years 11 months ago
Adaptive duplicate detection using learnable string similarity measures
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
Mikhail Bilenko, Raymond J. Mooney
POPL
2007
ACM
15 years 11 months ago
Scrap your boilerplate with XPath-like combinators
XML programming involves idioms for expressing `structure shyness' such as the descendant axis of XPath or the default templates of XSLT. We initiate a discussion of the rela...
Ralf Lämmel