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» Approximate data mining in very large relational data
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106
Voted
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
16 years 2 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
KDD
2001
ACM
118views Data Mining» more  KDD 2001»
16 years 2 months ago
Infominer: mining surprising periodic patterns
In this paper, we focus on mining surprising periodic patterns in a sequence of events. In many applications, e.g., computational biology, an infrequent pattern is still considere...
Jiong Yang, Wei Wang 0010, Philip S. Yu
SSD
2001
Springer
218views Database» more  SSD 2001»
15 years 6 months ago
Efficient Mining of Spatiotemporal Patterns
The problem of mining spatiotemporal patterns is finding sequences of events that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of object...
Ilias Tsoukatos, Dimitrios Gunopulos
143
Voted
KDD
2012
ACM
263views Data Mining» more  KDD 2012»
13 years 4 months ago
Integrating community matching and outlier detection for mining evolutionary community outliers
Temporal datasets, in which data evolves continuously, exist in a wide variety of applications, and identifying anomalous or outlying objects from temporal datasets is an importan...
Manish Gupta, Jing Gao, Yizhou Sun, Jiawei Han
LREC
2010
346views Education» more  LREC 2010»
15 years 3 months ago
Twitter as a Corpus for Sentiment Analysis and Opinion Mining
Microblogging today has become a very popular communication tool among Internet users. Millions of users share opinions on different aspects of life everyday. Therefore microblogg...
Alexander Pak, Patrick Paroubek