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» Mining Patterns in Long Sequential Data with Noise
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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 8 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
14 years 8 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
NBIS
2010
Springer
13 years 5 months ago
Mining Association Rules Consisting of Download Servers from Distributed Honeypot Observation
This paper aims to find interested association rules, known as data mining technique, out of the dataset of downloading logs by focusing on the coordinated activity among downloadi...
Masayuki Ohrui, Hiroaki Kikuchi, Masato Terada
DASFAA
2006
IEEE
133views Database» more  DASFAA 2006»
14 years 1 months ago
Mining Spatio-temporal Association Rules, Sources, Sinks, Stationary Regions and Thoroughfares in Object Mobility Databases
Abstract. As mobile devices proliferate and networks become more locationaware, the corresponding growth in spatio-temporal data will demand analysis techniques to mine patterns th...
Florian Verhein, Sanjay Chawla
KDD
2004
ACM
157views Data Mining» more  KDD 2004»
14 years 1 months ago
Fast mining of spatial collocations
Spatial collocation patterns associate the co-existence of nonspatial features in a spatial neighborhood. An example of such a pattern can associate contaminated water reservoirs ...
Xin Zhang, Nikos Mamoulis, David W. Cheung, Yutao ...