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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 7 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 ...
SAC
2010
ACM
14 years 1 months ago
Mining temporal relationships among categories
Temporal text mining deals with discovering temporal patterns in text over a period of time. A Theme Evolution Graph (TEG) is used to visualize when new themes are created and how...
Saket S. R. Mengle, Nazli Goharian
GIS
2006
ACM
14 years 7 months ago
Mining frequent geographic patterns with knowledge constraints
The large amount of patterns generated by frequent pattern mining algorithms has been extensively addressed in the last few years. In geographic pattern mining, besides the large ...
Luis Otávio Alvares, Paulo Martins Engel, S...
IDA
2009
Springer
13 years 4 months ago
Efficient Vertical Mining of Frequent Closures and Generators
Abstract. The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs). However, only few m...
Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, R...
CORR
2010
Springer
219views Education» more  CORR 2010»
13 years 6 months ago
Finding Sequential Patterns from Large Sequence Data
Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mini...
Mahdi Esmaeili, Fazekas Gabor