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ESWA
2006
139views more  ESWA 2006»
13 years 7 months ago
An efficient data mining approach for discovering interesting knowledge from customer transactions
Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
Show-Jane Yen, Yue-Shi Lee
IUI
2010
ACM
14 years 2 months ago
From documents to tasks: deriving user tasks from document usage patterns
A typical knowledge worker is involved in multiple tasks and switches frequently between them every work day. These frequent switches become expensive because each task switch req...
Oliver Brdiczka
ICDM
2010
IEEE
121views Data Mining» more  ICDM 2010»
13 years 5 months ago
Recommending Social Events from Mobile Phone Location Data
A city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can change the way one de...
Daniele Quercia, Neal Lathia, Francesco Calabrese,...
GEOINFORMATICA
2006
102views more  GEOINFORMATICA 2006»
13 years 7 months ago
Mining Co-Location Patterns with Rare Events from Spatial Data Sets
Abstract A co-location pattern is a group of spatial features/events that are frequently co-located in the same region. For example, human cases of West Nile Virus often occur in r...
Yan Huang, Jian Pei, Hui Xiong
KDD
2010
ACM
232views Data Mining» more  KDD 2010»
13 years 11 months ago
Discovering frequent patterns in sensitive data
Discovering frequent patterns from data is a popular exploratory technique in data mining. However, if the data are sensitive (e.g. patient health records, user behavior records) ...
Raghav Bhaskar, Srivatsan Laxman, Adam Smith, Abhr...