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» Large Scale Data Mining: Challenges and Responses
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CLEANDB
2006
ACM
142views Database» more  CLEANDB 2006»
15 years 8 months ago
QUEST: QUery-driven Exploration of Semistructured Data with ConflicTs and Partial Knowledge
An important reality when integrating scientific data is the fact that data may often be "missing", partially specified, or conflicting. Therefore, in this paper, we pre...
Yan Qi 0002, K. Selçuk Candan, Maria Luisa ...
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
15 years 11 months ago
Evolving En-Route Caching Strategies for the Internet
Nowadays, large distributed databases are commonplace. Client applications increasingly rely on accessing objects from multiple remote hosts. The Internet itself is a huge network ...
Jürgen Branke, Pablo Funes, Frederik Thiele
CONCURRENCY
2010
130views more  CONCURRENCY 2010»
15 years 6 months ago
Enabling high-speed asynchronous data extraction and transfer using DART
As the complexity and scale of current scientific and engineering applications grow, managing and transporting the large amounts of data they generate is quickly becoming a signif...
Ciprian Docan, Manish Parashar, Scott Klasky
BMCBI
2010
138views more  BMCBI 2010»
15 years 6 months ago
A database and API for variation, dense genotyping and resequencing data
Background: Advances in sequencing and genotyping technologies are leading to the widespread availability of multi-species variation data, dense genotype data and large-scale rese...
Daniel Rios, William M. McLaren, Yuan Chen, Ewan B...
175
Voted
PRL
2010
158views more  PRL 2010»
15 years 4 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain