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 .4.C-IOg which allows a unified treatment of both the relational and structural features of data. A generality order and a downward refinement operator for AC-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.
Inducing Multi-Level Association Rules for Multiple Relations
LISI, Francesca Alessandra;MALERBA, Donato
2004-01-01
Abstract
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 .4.C-IOg which allows a unified treatment of both the relational and structural features of data. A generality order and a downward refinement operator for AC-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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
