A Mining Algorithm Using Property Items Extracted from Sampled Examples

Authors:
Jun-Ichi Motoyama;Shinpei Urazawa;Tomofumi Nakano;Nobuhiro Inuzuka
Affiliations:
Nagoya Institute of Technology, Gokiso-cho Showa, Nagoya 466-8555, Japan;Nagoya Institute of Technology, Gokiso-cho Showa, Nagoya 466-8555, Japan;Nagoya Institute of Technology, Gokiso-cho Showa, Nagoya 466-8555, Japan;Nagoya Institute of Technology, Gokiso-cho Showa, Nagoya 466-8555, Japan
Venue:
Inductive Logic Programming
Year:
2007

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Abstract

This paper proposes a mining algorithm for relational frequent patterns based on a bottom-up property extraction from examples. The extracted properties, called property items, are used to construct patterns by a level-wise way like Apriori. The property items are assumed to have a special form, which is defined in terms of mode declaration of predicates. The algorithm produces frequent itemsets as patterns without duplication in the sense of logical equivalence. It is implemented as a system called Mapixand is evaluated with four different datasets with comparison to Warmr. Mapixhad large advantage in runtime.