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126
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PAKDD
2007
ACM
184views Data Mining» more  PAKDD 2007»
15 years 9 months ago
A Fast Algorithm for Finding Correlation Clusters in Noise Data
Abstract. Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clusterin...
Jiuyong Li, Xiaodi Huang, Clinton Selke, Jianming ...
ICDM
2006
IEEE
98views Data Mining» more  ICDM 2006»
15 years 9 months ago
What is the Dimension of Your Binary Data?
Many 0/1 datasets have a very large number of variables; however, they are sparse and the dependency structure of the variables is simpler than the number of variables would sugge...
Nikolaj Tatti, Taneli Mielikäinen, Aristides ...
ICDM
2005
IEEE
143views Data Mining» more  ICDM 2005»
15 years 9 months ago
A Computational Framework for Taxonomic Research: Diagnosing Body Shape within Fish Species Complexes
It is estimated that ninety percent of the world’s species have yet to be discovered and described. The main reason for the slow pace of new species description is that the scie...
Yixin Chen, Henry L. Bart Jr., Shuqing Huang, Huim...
132
Voted
ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
15 years 9 months ago
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...
Thomas George, Srujana Merugu
119
Voted
PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
15 years 9 months ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree