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» Business Process Understanding: Mining Many Datasets
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VLDB
2007
ACM
179views Database» more  VLDB 2007»
14 years 7 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han
WWW
2003
ACM
14 years 8 months ago
Mining topic-specific concepts and definitions on the web
Traditionally, when one wants to learn about a particular topic, one reads a book or a survey paper. With the rapid expansion of the Web, learning in-depth knowledge about a topic...
Bing Liu, Chee Wee Chin, Hwee Tou Ng
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 5 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
BMCBI
2005
116views more  BMCBI 2005»
13 years 7 months ago
Which gene did you mean?
Computational Biology needs computer-readable information records. Increasingly, meta-analysed and pre-digested information is being used in the follow up of high throughput exper...
Barend Mons
SDM
2008
SIAM
117views Data Mining» more  SDM 2008»
13 years 9 months ago
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Yijun Sun, Sinisa Todorovic, Steve Goodison