Name
Title | ||
|---|---|---|
NARFO Algorithm: Mining Non-redundant and Generalized Association Rules Based on Fuzzy Ontologies |
Abstract | ||
|---|---|---|
Traditional approaches for mining generalized association rules are based only on database contents, and focus oil exact matches among items. However, in many applications, the use of some background knowledge, as ontologies, call enhance the discovery process and generate semantically richer rules. In this way, this paper Proposes the NARFO algorithm, a new algorithm for mining non-redundant and generalized association rules based on Fuzzy ontologies. Fuzzy ontology is used as background knowledge, to support the discovery process and the generation Of rules. One contribution of this work is the generalization of non-frequent itemsets that helps to extract important and meaningful knowledge. NARFO algorithm also contributes at post-processing stage with its generalization and redundancy treatment. Our experiments showed that the number of rules had been reduced considerably, without redundancy, obtaining 63.63% average reduction in comparison with XSSDM algorithm. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-01347-8_35 | Lecture Notes in Business Information Processing |
Keywords | Field | DocType |
Data Mining,Generalized Association Rules,Redundant Rules,Fuzzy Ontology | Ontology (information science),Data mining,Computer science,Algorithm,Association rule learning,Fuzzy ontology,Redundancy (engineering),Artificial intelligence,Business process discovery,Machine learning | Conference |
Volume | ISSN | Citations |
24 | 1865-1348 | 10 |
PageRank | References | Authors |
0.57 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Garcia Miani | 1 | 13 | 1.33 |
| Cristiane A. Yaguinuma | 2 | 30 | 4.79 |
| Marilde T. P. Santos | 3 | 19 | 2.80 |
| Mauro Biajiz | 4 | 45 | 7.73 |