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» Structure Discovery from Sequential Data
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SIGMOD
1998
ACM
150views Database» more  SIGMOD 1998»
15 years 1 months ago
Extracting Schema from Semistructured Data
Semistructured data is characterized by the lack of any fixed and rigid schema, although typically the data hassomeimplicitstructure. While thelack offixedschemamakesextracting ...
Svetlozar Nestorov, Serge Abiteboul, Rajeev Motwan...
AI
2002
Springer
14 years 9 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
JBI
2008
137views Bioinformatics» more  JBI 2008»
14 years 9 months ago
Mining sequential patterns for protein fold recognition
Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utiliz...
Themis P. Exarchos, Costas Papaloukas, Christos La...
79
Voted
BMCBI
2010
182views more  BMCBI 2010»
14 years 9 months ago
Beyond co-localization: inferring spatial interactions between sub-cellular structures from microscopy images
Background: Sub-cellular structures interact in numerous direct and indirect ways in order to fulfill cellular functions. While direct molecular interactions crucially depend on s...
Jo A. Helmuth, Grégory Paul, Ivo F. Sbalzar...
60
Voted
OOPSLA
2005
Springer
15 years 3 months ago
Lifting sequential graph algorithms for distributed-memory parallel computation
This paper describes the process used to extend the Boost Graph Library (BGL) for parallel operation with distributed memory. The BGL consists of a rich set of generic graph algor...
Douglas Gregor, Andrew Lumsdaine