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Structure induction by lossless graph compression

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1 Author(s)
Peshkin, L. ; Center for Biomed. Inf., Harvard Med. Sch., Boston, MA

This work is motivated by the necessity to automate the discovery of structure in vast and ever-growing collection of relational data commonly represented as graphs, for example genomic networks. A novel algorithm, dubbed Graphitour, for structure induction by lossless graph compression is presented and illustrated by a clear and broadly known case of nested structure in a DNA molecule. This work extends to graphs some well established approaches to grammatical inference previously applied only to strings. The bottom-up graph compression problem is related to the maximum cardinality (non-bipartite) maximum cardinality matching problem. The algorithm accepts a variety of graph types including directed graphs and graphs with labeled nodes and arcs. The resulting structure could be used for representation and classification of graphs

Published in:

Data Compression Conference, 2007. DCC '07

Date of Conference:

27-29 March 2007