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DATAMINE
1999
108views more  DATAMINE 1999»
13 years 7 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 8 months ago
Correlation search in graph databases
Correlation mining has gained great success in many application domains for its ability to capture the underlying dependency between objects. However, the research of correlation ...
Yiping Ke, James Cheng, Wilfred Ng
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 6 months ago
Scalable similarity search with optimized kernel hashing
Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
Junfeng He, Wei Liu, Shih-Fu Chang
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
KDD
2006
ACM
120views Data Mining» more  KDD 2006»
14 years 8 months ago
Hierarchical topic segmentation of websites
In this paper, we consider the problem of identifying and segmenting topically cohesive regions in the URL tree of a large website. Each page of the website is assumed to have a t...
Ravi Kumar, Kunal Punera, Andrew Tomkins