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Mining tree queries in a graph
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Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining table of contents
Chicago, Illinois, USA
SESSION: Research track paper table of contents
Pages: 61 - 69  
Year of Publication: 2005
ISBN:1-59593-135-X
Authors
Bart Goethals  Universiteit Antwerpen
Eveline Hoekx  Universiteit Hasselt
Jan Van den Bussche  Universiteit Hasselt
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present an algorithm for mining tree-shaped patterns in a large graph. Novel about our class of patterns is that they can contain constants, and can contain existential nodes which are not counted when determining the number of occurrences of the pattern in the graph. Our algorithm has a number of provable optimality properties, which are based on the theory of conjunctive database queries. We propose a database-oriented implementation in SQL, and report upon some initial experimental results obtained with our implementation on graph data about food webs, about protein interactions, and about citation analysis.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Bart Goethals: colleagues
Eveline Hoekx: colleagues
Jan Van den Bussche: colleagues