|
Title:
|
PUSHING CONSTRAINTS IN ASSOCIATION RULE MINING: AN ONTOLOGY-BASED APPROACH |
|
Author(s):
|
Andrea Bellandi , Barbara Furletti , Valerio Grossi , Andrea Romei |
|
ISBN:
|
978-972-8924-44-7 |
|
Editors:
|
Pedro Isaías , Miguel Baptista Nunes and João Barroso (associate editors Luís Rodrigues and Patrícia Barbosa) |
|
Year:
|
2007 |
|
Edition:
|
V I, 2 |
|
Keywords:
|
Data Mining, association rules, ontology, domain-specific constraints. |
|
Type:
|
Full Paper |
|
First Page:
|
179 |
|
Last Page:
|
186 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
This paper proposes an integrated framework for the extraction of constraint-based multi-level association rules with the
aid of an ontology. The latter, which represents an enriched taxonomy, is used to describe the application domain by
means of data properties. Defining or updating these properties is a simple task and does not imply changing the items
hierarchy, or the implementation level of our framework. The system enables the definition of domain-specific
constraints, by using the ontology to filter the instances used in the association rule mining process. This can improve the
quality of the extracted association rules and make them more interesting and easy to understand. We describe our
framework, also including examples of queries based on real-data. |
|
|
|
|
|
|
