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HPCC
2005
Springer

High Performance Subgraph Mining in Molecular Compounds

12 years 1 months ago
High Performance Subgraph Mining in Molecular Compounds
Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques particularly relevant. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely a dynamic partitioning of the search space, a distribution process based on a peer-topeer communication framework, and a novel receiver-initiated, load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening dataset, where the approach attains close-to linear speedup in a network of workstations.
Giuseppe Di Fatta, Michael R. Berthold
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where HPCC
Authors Giuseppe Di Fatta, Michael R. Berthold
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