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» Introduction to Data Mining and Knowledge Discovery
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DAGSTUHL
2007
14 years 11 months ago
Discovering Knowledge from Local Patterns with Global Constraints
It is well known that local patterns are at the core of a lot of knowledge which may be discovered from data. Nevertheless, use of local patterns is limited by their huge number an...
Bruno Crémilleux, Arnaud Soulet
IJBIDM
2011
127views more  IJBIDM 2011»
14 years 4 months ago
WebUser: mining unexpected web usage
: Web usage mining has been much concentrated on the discovery of relevant user behaviours from Web access record data. In this paper, we present WebUser, an approach to discover u...
Dong (Haoyuan) Li, Anne Laurent, Pascal Poncelet
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
15 years 2 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
DATAMINE
2002
135views more  DATAMINE 2002»
14 years 9 months ago
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
: Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these tec...
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakag...
CORR
2010
Springer
173views Education» more  CORR 2010»
14 years 7 months ago
Mining Multi-Level Frequent Itemsets under Constraints
Mining association rules is a task of data mining, which extracts knowledge in the form of significant implication relation of useful items (objects) from a database. Mining multi...
Mohamed Salah Gouider, Amine Farhat