A multiobjective variant of the Subdue graph mining algorithm based on the NSGA-II selection mechanism

In this work we propose a Pareto-based multi-objective search strategy for subgraph mining in structural databases. The method is an extension of Subdue, a classical graph-based knowledge discovery algorithm, and it is thus called MultiObjective Subdue (MOSubdue). MOSubdue incorporates the NSGA-II&#...

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Bibliographic Details
Main Authors: Shelokar, Prakash, Quirin, Arnaud, Cordón, Óscar
Format: Conference Proceeding
Language:English
Subjects:
Complexity theory
Data mining
Measurement
Optimization
Search problems
Web sites
Online Access:Request full text
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Description
Summary:In this work we propose a Pareto-based multi-objective search strategy for subgraph mining in structural databases. The method is an extension of Subdue, a classical graph-based knowledge discovery algorithm, and it is thus called MultiObjective Subdue (MOSubdue). MOSubdue incorporates the NSGA-II's crowding selection mechanism in order to retrieve a well distributed Pareto optimal set of meaningful subgraphs showing different optimal trade-offs between support and complexity, in a single run. The good performance of the proposed approach is empirically demonstrated by using a reallife data set concerning the analysis of web sites.
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2010.5586400