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SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
15 years 6 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh
KDD
1998
ACM
183views Data Mining» more  KDD 1998»
15 years 1 months ago
Mining Generalized Association Rules and Sequential Patterns Using SQL Queries
Database integration of mining is becoming increasingly important with tile installation of larger and larger data warehouses built around relational database technology. Most of ...
Shiby Thomas, Sunita Sarawagi
91
Voted
WWW
2010
ACM
15 years 4 months ago
Find me if you can: improving geographical prediction with social and spatial proximity
Geography and social relationships are inextricably intertwined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data re...
Lars Backstrom, Eric Sun, Cameron Marlow
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
15 years 10 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
JPDC
2008
134views more  JPDC 2008»
14 years 9 months ago
Middleware for data mining applications on clusters and grids
This paper gives an overview of two middleware systems that have been developed over the last 6 years to address the challenges involved in developing parallel and distributed imp...
Leonid Glimcher, Ruoming Jin, Gagan Agrawal