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WWW
2001
ACM
16 years 5 months ago
Intelligent crawling on the World Wide Web with arbitrary predicates
The enormous growth of the world wide web in recent years has made it important to perform resource discovery e ciently. Consequently, several new ideas have been proposed in rece...
Charu C. Aggarwal, Fatima Al-Garawi, Philip S. Yu
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
16 years 5 months ago
A multi-relational approach to spatial classification
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Richard Frank, Martin Ester, Arno Knobbe
KDD
2007
ACM
141views Data Mining» more  KDD 2007»
16 years 5 months ago
Mining favorable facets
The importance of dominance and skyline analysis has been well recognized in multi-criteria decision making applications. Most previous studies assume a fixed order on the attribu...
Raymond Chi-Wing Wong, Jian Pei, Ada Wai-Chee Fu, ...
162
Voted
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 5 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
16 years 5 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
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