Bellandi A., Furletti B., Grossi V., Romei A.
Association Rules Ontology Data mining
This paper proposes an integrated framework for extracting Constraint-based Multi-level Association Rules with an ontology support. The system permits the definition of a set of domain-specific constraints on a specific domain ontology, and to query the ontology for filtering the instances used in the association rule mining process. This method can improve the quality of the extracted associations rules in terms of relevance and understandability.
Source: C&O:RR-2007 - International Workshop on Contexts and Ontologies: Representation and Reasoning, pp. 10–19, Roskilde University, Denmark, 21 August 2007
Publisher: CEUR-WS.org, Aachen, DEU
@inproceedings{oai:it.cnr:prodotti:272222, title = {Ontology-Driven Association Rule Extraction: A Case Study}, author = {Bellandi A. and Furletti B. and Grossi V. and Romei A.}, publisher = {CEUR-WS.org, Aachen, DEU}, booktitle = {C\&O:RR-2007 - International Workshop on Contexts and Ontologies: Representation and Reasoning, pp. 10–19, Roskilde University, Denmark, 21 August 2007}, year = {2007} }
MUSING
MUlti-Industry, Semantic-based Next Generation Business INtelliGence