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DIS
2004
Springer

Predictive Graph Mining

13 years 9 months ago
Predictive Graph Mining
Abstract. Graph mining approaches are extremely popular and effective in molecular databases. The vast majority of these approaches first derive interesting, i.e. frequent, patterns and then use these as features to build predictive models. Rather than building these models in a two step indirect way, the SMIREP system introduced in this paper, derives predictive rule models from molecular data directly. SMIREP combines the SMILES and SMARTS representation languages that are popular in computational chemistry with the IREP rule-learning algorithm by F¨urnkranz. Even though SMIREP is focused on SMILES, its principles are also applicable to graph mining problems in other domains. SMIREP is experimentally evaluated on two benchmark databases.
Andreas Karwath, Luc De Raedt
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where DIS
Authors Andreas Karwath, Luc De Raedt
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