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» Set cover algorithms for very large datasets
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SIGMOD
2004
ACM
92views Database» more  SIGMOD 2004»
14 years 8 months ago
Online Maintenance of Very Large Random Samples
Random sampling is one of the most fundamental data management tools available. However, most current research involving sampling considers the problem of how to use a sample, and...
Chris Jermaine, Abhijit Pol, Subramanian Arumugam
WIDM
2006
ACM
14 years 2 months ago
Identifying redundant search engines in a very large scale metasearch engine context
For a given set of search engines, a search engine is redundant if its searchable contents can be found from other search engines in this set. In this paper, we propose a method t...
Ronak Desai, Qi Yang, Zonghuan Wu, Weiyi Meng, Cle...
ICTAI
2002
IEEE
14 years 1 months ago
Data Mining for Selective Visualization of Large Spatial Datasets
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
Shashi Shekhar, Chang-Tien Lu, Pusheng Zhang, Ruli...
ESA
2010
Springer
185views Algorithms» more  ESA 2010»
13 years 9 months ago
Fast Routing in Very Large Public Transportation Networks Using Transfer Patterns
We show how to route on very large public transportation networks (up to half a billion arcs) with average query times of a few milliseconds. We take into account many realistic fe...
Hannah Bast, Erik Carlsson, Arno Eigenwillig, Robe...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
14 years 8 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui