Multi-relational Pattern Mining Based-on Combination of Properties with Preserving Their Structure in Examples
We propose an algorithm for multi-relational pattern mining through the problem established in WARMR. In order to overcome the combinatorial problem of large pattern space, another algorithm MAPIX restricts patterns into combination of basic patterns, called properties. A property is defined as a set of literals appeared in examples and is of an extended attribute-value form. Advantage of MAPIX is to make patterns from pattern fragments occurred in examples. Many patterns which are not appeared in examples are not tested. Although the range of patterns is clear and MAPIX enumerates them efficiently, a large part of patterns are out of the range. The proposing algorithm keeps the advantage and extends the way of combination of properties. The algorithm combines properties as they appeared in examples, we call it structure preserving combination.
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