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» MapReduce: Simplified Data Processing on Large Clusters
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JGTOOLS
2008
100views more  JGTOOLS 2008»
13 years 7 months ago
Proximity Cluster Trees
Hierarchical spatial data structures provide a means for organizing data for efficient processing. Most spatial data structures are optimized for performing queries, such as inters...
Elena Jakubiak Hutchinson, Sarah F. Frisken, Ronal...
VLDB
2002
ACM
154views Database» more  VLDB 2002»
13 years 7 months ago
I/O-Conscious Data Preparation for Large-Scale Web Search Engines
Given that commercial search engines cover billions of web pages, efficiently managing the corresponding volumes of disk-resident data needed to answer user queries quickly is a f...
Maxim Lifantsev, Tzi-cker Chiueh
TSP
2008
167views more  TSP 2008»
13 years 6 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
CIKM
2009
Springer
14 years 2 months ago
SPIDER: a system for scalable, parallel / distributed evaluation of large-scale RDF data
RDF is a data model for representing labeled directed graphs, and it is used as an important building block of semantic web. Due to its flexibility and applicability, RDF has bee...
Hyunsik Choi, Jihoon Son, YongHyun Cho, Min Kyoung...
SIGMOD
2009
ACM
136views Database» more  SIGMOD 2009»
14 years 8 months ago
A comparison of approaches to large-scale data analysis
There is currently considerable enthusiasm around the MapReduce (MR) paradigm for large-scale data analysis [17]. Although the basic control flow of this framework has existed in ...
Andrew Pavlo, Erik Paulson, Alexander Rasin, Danie...