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» Mining interesting sets and rules in relational databases
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SDM
2008
SIAM
130views Data Mining» more  SDM 2008»
13 years 11 months ago
Mining Sequence Classifiers for Early Prediction
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
NAR
2008
142views more  NAR 2008»
13 years 9 months ago
CMGSDB: integrating heterogeneous Caenorhabditis elegans data sources using compositional data mining
CMGSDB (Database for Computational Modeling of Gene Silencing) is an integration of heterogeneous data sources about Caenorhabditis elegans with capabilities for compositional dat...
Amrita Pati, Ying Jin, Karsten Klage, Richard F. H...
ACMICEC
2007
ACM
144views ECommerce» more  ACMICEC 2007»
14 years 1 months ago
Needs-based analysis of online customer reviews
Needs-based analysis lies at the intersection of product marketing and new product development. It is the study of why consumers purchase and what they do with those purchases. In...
Thomas Y. Lee
VLDB
1999
ACM
188views Database» more  VLDB 1999»
14 years 1 months ago
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
Discovering sequential patterns is an important problem in data mining with a host of application domains including medicine, telecommunications, and the World Wide Web. Conventio...
Minos N. Garofalakis, Rajeev Rastogi, Kyuseok Shim
DATAMINE
1999
108views more  DATAMINE 1999»
13 years 9 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri