Publikation: Edgar: the Embedding-baseD GrAph MineR
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2006
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MLG 2006 : Proceedings of the International Workshop on Mining and Learning with Graphs : in conjunction with ECML / PKDD 2006. Berlin, 2006. 2006
Zusammenfassung
In this paper we present the novel graph mining algorithm Edgar which is based on the well-known gSpan algorithm. The need for anothersubgraph miner results from procedural abstraction (an important technique to reduce code size in embedded systems). Assembler code is represented as a data flow graph and subgraph mining on this graph returns frequent code fragments that can be extracted into procedures. When mining for procedural abstraction, it is not the number of data flow graphs in which a fragment occurs that is important but the number of all the non-overlapping occurrences in all graphs. Several changes in the mining process have therefore become necessary. As traditional pruning strategies are inappropriate, Edgar uses a new embedding-based frequency; on average, saves 160% more instructions compared to classical approaches.
Zusammenfassung in einer weiteren Sprache
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004 Informatik
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graph mining
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MLG in conjunction with ECML/PKDD, 2006, Berlin
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WÖRLEIN, Marc, Alexander DREWEKE, Thorsten MEINL, Ingrid FISCHER, Michael PHILIPPSEN, 2006. Edgar: the Embedding-baseD GrAph MineR. MLG in conjunction with ECML/PKDD. Berlin, 2006. In: MLG 2006 : Proceedings of the International Workshop on Mining and Learning with Graphs : in conjunction with ECML / PKDD 2006. Berlin, 2006. 2006BibTex
@inproceedings{Worlein2006Edgar-5877,
year={2006},
title={Edgar: the Embedding-baseD GrAph MineR},
booktitle={MLG 2006 : Proceedings of the International Workshop on Mining and Learning with Graphs : in conjunction with ECML / PKDD 2006. Berlin, 2006},
author={Wörlein, Marc and Dreweke, Alexander and Meinl, Thorsten and Fischer, Ingrid and Philippsen, Michael}
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<dcterms:abstract xml:lang="eng">In this paper we present the novel graph mining algorithm Edgar which is based on the well-known gSpan algorithm. The need for anothersubgraph miner results from procedural abstraction (an important technique to reduce code size in embedded systems). Assembler code is represented as a data flow graph and subgraph mining on this graph returns frequent code fragments that can be extracted into procedures. When mining for procedural abstraction, it is not the number of data flow graphs in which a fragment occurs that is important but the number of all the non-overlapping occurrences in all graphs. Several changes in the mining process have therefore become necessary. As traditional pruning strategies are inappropriate, Edgar uses a new embedding-based frequency; on average, saves 160% more instructions compared to classical approaches.</dcterms:abstract>
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