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Inducing multi-level association rules from multiple relations
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DOI：10.1023/B:MACH.0000023151.65011.a3.png)
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Abstract
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Recently there has been growing interest both to extend ILP to description logics and to apply it to knowledge discovery in databases. In this paper we present a novel approach to association rule mining which deals with multiple levels of description granularity. It relies on the hybrid language AL-log which allows a unified treatment of both the relational and structural features of data. A generality order and a downward refinement operator for AL-log pattern spaces is defined on the basis of query subsumption. This framework has been implemented in SPADA, an ILP system for mining multi-level association rules from spatial data. As an illustrative example, we report experimental results obtained by running the new version of SPADA on geo-referenced census data of Manchester Stockport.
Keywords:
inductive logic programming
description logics
spatial data mining
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