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ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
14 years 17 days ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
SIGKDD
2000
237views more  SIGKDD 2000»
13 years 6 months ago
The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation
Advances in data collection and storage have allowed organizations to create massive, complex and heterogeneous databases, which have stymied traditional methods of data analysis....
Stephen D. Bay, Dennis F. Kibler, Michael J. Pazza...
SIGMOD
2001
ACM
193views Database» more  SIGMOD 2001»
14 years 6 months ago
Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data
The similarity join is an important database primitive which has been successfully applied to speed up applications such as similarity search, data analysis and data mining. The s...
Christian Böhm, Bernhard Braunmüller, Fl...
CIKM
2006
Springer
13 years 10 months ago
Mining compressed commodity workflows from massive RFID data sets
Radio Frequency Identification (RFID) technology is fast becoming a prevalent tool in tracking commodities in supply chain management applications. The movement of commodities thr...
Hector Gonzalez, Jiawei Han, Xiaolei Li
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
14 years 9 days ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester