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» Massive Semantic Web data compression with MapReduce
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HPDC
2010
IEEE
13 years 6 months ago
Massive Semantic Web data compression with MapReduce
The Semantic Web consists of many billions of statements made of terms that are either URIs or literals. Since these terms usually consist of long sequences of characters, an effe...
Jacopo Urbani, Jason Maassen, Henri E. Bal
SIGMOD
2010
ACM
321views Database» more  SIGMOD 2010»
13 years 9 months ago
HadoopDB in action: building real world applications
HadoopDB is a hybrid of MapReduce and DBMS technologies, designed to meet the growing demand of analyzing massive datasets on very large clusters of machines. Our previous work ha...
Azza Abouzied, Kamil Bajda-Pawlikowski, Jiewen Hua...
SEMWEB
2010
Springer
13 years 2 months ago
Signal/Collect: Graph Algorithms for the (Semantic) Web
The Semantic Web graph is growing at an incredible pace, enabling opportunities to discover new knowledge by interlinking and analyzing previously unconnected data sets. This confr...
Philip Stutz, Abraham Bernstein, William Cohen
SEMCO
2009
IEEE
13 years 11 months ago
Building a Semantic Web of Things: Issues and Perspectives in Information Compression
The paper surveys some relevant issues related to data management in pervasive environments. Particularly, it focuses on the compression of semantic annotations for building so ca...
Floriano Scioscia, Michele Ruta
WEBDB
2010
Springer
173views Database» more  WEBDB 2010»
13 years 10 months ago
Manimal: Relational Optimization for Data-Intensive Programs
The MapReduce distributed programming framework is very popular, but currently lacks the optimization techniques that have been standard with relational database systems for many ...
Michael J. Cafarella, Christopher Ré