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» Mining Very Large Databases
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123
Voted
VLDB
2005
ACM
144views Database» more  VLDB 2005»
15 years 9 months ago
Bidirectional Expansion For Keyword Search on Graph Databases
Relational, XML and HTML data can be represented as graphs with entities as nodes and relationships as edges. Text is associated with nodes and possibly edges. Keyword search on s...
Varun Kacholia, Shashank Pandit, Soumen Chakrabart...
138
Voted
NAR
2011
223views Computer Vision» more  NAR 2011»
14 years 6 months ago
HitPredict: a database of quality assessed protein-protein interactions in nine species
Despite the availability of a large number of protein– protein interactions (PPIs) in several species, researchers are often limited to using very small subsets in a few organis...
Ashwini Patil, Kenta Nakai, Haruki Nakamura
CDB
2004
Springer
172views Database» more  CDB 2004»
15 years 8 months ago
Constraint Database Solutions to the Genome Map Assembly Problem
Abstract. Long DNA sequences have to be cut using restriction enzymes into small fragments whose lengths and/or nucleotide sequences can be analyzed by currently available technolo...
Viswanathan Ramanathan, Peter Z. Revesz
KDD
2002
ACM
119views Data Mining» more  KDD 2002»
16 years 3 months ago
On effective classification of strings with wavelets
In recent years, the technological advances in mapping genes have made it increasingly easy to store and use a wide variety of biological data. Such data are usually in the form o...
Charu C. Aggarwal
103
Voted
PAKDD
2005
ACM
94views Data Mining» more  PAKDD 2005»
15 years 9 months ago
Progressive Sampling for Association Rules Based on Sampling Error Estimation
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
Kun-Ta Chuang, Ming-Syan Chen, Wen-Chieh Yang