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» Informative sampling for large unbalanced data sets
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EMNLP
2006
15 years 2 months ago
Unsupervised Information Extraction Approach Using Graph Mutual Reinforcement
Information Extraction (IE) is the task of extracting knowledge from unstructured text. We present a novel unsupervised approach for information extraction based on graph mutual r...
Hany Hassan, Ahmed Hassan, Ossama Emam
CIKM
2008
Springer
15 years 3 months ago
Viability of in-house datamarting approaches for population genetics analysis of snp genotypes
Background: Databases containing very large amounts of SNP (Single Nucleotide Polymorphism) data are now freely available for researchers interested in medical and/or population g...
Jorge Amigo, Christopher Phillips, Antonio Salas
CIKM
2009
Springer
15 years 5 months ago
Efficient processing of group-oriented connection queries in a large graph
We study query processing in large graphs that are fundamental data model underpinning various social networks and Web structures. Given a set of query nodes, we aim to find the g...
James Cheng, Yiping Ke, Wilfred Ng
DOLAP
1998
ACM
15 years 5 months ago
Dynamic Maintenance of Multidimensional Range Data Partitioning for Parallel Data Processing
Star schema has been a typical model for both online transaction processing in traditional databases and online analytical processing in large data warehouses. In the star schema,...
Junping Sun, William I. Grosky
AIME
2009
Springer
15 years 5 months ago
Data-Efficient Information-Theoretic Test Selection
We use the concept of conditional mutual information (MI) to approach problems involving the selection of variables in the area of medical diagnosis. Computing MI requires estimate...
Marianne Mueller, Rómer Rosales, Harald Ste...