RUSE-WARMR: Rule Selection for Classifier Induction in Multi-Relational Data-Sets

• Tipo: Artigo em Revista Científica Internacional
• Data: 2008

Autores

Carlos Abreu Ferreira (Autor) Outra; Joao Gama (Autor) FEP; Vitor Santos Costa (Autor) FCUP

Revista

Título: 20Th Ieee International Conference on Tools with Artificial Intelligence

Vol. 1

Páginas: 369-386

ISSN: 1082-3409

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 5 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-004-5GA

DOI: 10.1109/ictai.2008.73

Abstract (EN): One of the major challenges in knowledge discovery is how to extract meaningful and useful knowledge from the complex structured data that one finds in Scientific and Technological applications. One approach is to explore the logic relations in the database and using, say, an Inductive Logic Programming (ILP) algorithm find descriptive and expressive patterns. These patterns can then be used as features to characterize the target concept, The effectiveness of these algorithms depends both upon the algorithm we use to generate the patterns and upon the classifier Rule mining provides an excellent framework for efficiently mining the interesting patterns that are relevant. We propose a novel method to select discriminative patterns and evaluate the effectiveness of this method on a complex discovery application of practical interest.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8