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IS
2007
9 years 10 months ago
Business process mining: An industrial application
Contemporary information systems (e.g., WfM, ERP, CRM, SCM, and B2B systems) record business events in so-called event logs. Business process mining takes these logs to discover p...
Wil M. P. van der Aalst, Hajo A. Reijers, A. J. M....
SIGKDD
2008
248views more  SIGKDD 2008»
9 years 10 months ago
Web data mining: exploring hyperlinks, contents, and usage data
This paper presents a review of the book "Web Data Mining - Exploring Hyperlinks, Contents, and Usage Data" by Bing Liu. The review concludes that the breadth and depth ...
Olfa Nasraoui
SIGKDD
2008
113views more  SIGKDD 2008»
9 years 10 months ago
On exploiting the power of time in data mining
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
Mirko Böttcher, Frank Höppner, Myra Spil...
FGCS
2007
86views more  FGCS 2007»
9 years 10 months ago
A grid-based approach for enterprise-scale data mining
Abstract— We describe a grid-based approach for enterprisescale data mining that leverages database technology for I/O parallelism, and on-demand compute servers for compute para...
Ramesh Natarajan, Radu Sion, Thomas Phan
ESWA
2007
178views more  ESWA 2007»
9 years 10 months ago
Educational data mining: A survey from 1995 to 2005
ct 7 Currently there is an increasing interest in data mining and educational systems, making educational data mining as a new growing 8 research community. This paper surveys the ...
Cristóbal Romero, Sebastián Ventura
JIIS
2006
147views more  JIIS 2006»
9 years 10 months ago
Mining sequential patterns from data streams: a centroid approach
In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...
Alice Marascu, Florent Masseglia
JIIS
2006
124views more  JIIS 2006»
9 years 10 months ago
An efficient approach to mining indirect associations
Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has be...
Qian Wan, Aijun An
KAIS
2008
79views more  KAIS 2008»
9 years 10 months ago
Top 10 algorithms in data mining
This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, Page...
Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep ...
KAIS
2008
150views more  KAIS 2008»
9 years 10 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng
JCP
2006
139views more  JCP 2006»
9 years 10 months ago
Generalized Sequential Pattern Mining with Item Intervals
Sequential pattern mining is an important data mining method with broad applications that can extract frequent sequences while maintaining their order. However, it is important to ...
Yu Hirate, Hayato Yamana
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