Analyzing transitive rules on a hybrid concept discovery system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5572 LNAI, Issue , 2009, Pages 227-234

  Kavurucu, Yusuf ^a   Senkul, Pinar ^a   Toroslu, Ismail Hakki ^a  

^a MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Concept Discovery; ILP; MRDM; Transitive Rule

Indexed keywords

APRIORI; APRIORI ALGORITHMS; ASSOCIATION RULE MINING; CONCEPT DISCOVERY; DISCOVERY SYSTEMS; HIGH QUALITY; HYBRID CONCEPTS; ILP; KNOWLEDGE DISCOVERY SYSTEMS; MRDM; SEARCH SPACES; TARGET CONCEPT; TRANSITIVE RULE;

ARTIFICIAL INTELLIGENCE; ASSOCIATIVE PROCESSING;

TARGETS;

EID: 70350635367     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02319-4_27     Document Type: Conference Paper

References (12)

1. Džeroski, S.: Multi-relational data mining: an introduction. SIGKDD Explorations 5(1), 1-16 (2003)
2. Muggleton, S.: Inductive Logic Programming. In: The MIT Encyclopedia of the Cognitive Sciences (MITECS). MIT Press, Cambridge (1999)
3. Kavurucu, Y., Senkul, P., Toroslu, I.H.: Confidence-based concept discovery in multi-relational data mining. In: International Conference on Data Mining and Applications (ICDMA), Hong Kong, pp. 446-451 (March 2008)
4. Kavurucu, Y., Senkul, P., Toroslu, I.H.: Aggregation in confidence-based concept discovery for multi-relational data mining. In: IADIS European Conference on Data Mining (ECDM), Amsterdam, Netherland, pp. 43-50 (July 2008)
5. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules. In: Advances in Knowledge Discovery and Data Mining, pp. 307-328. AAAI/MIT Press (1996)
6. Quinlan, J.R.: Learning logical definitions from relations. Mach. Learn. 5(3), 239-266 (1990)
7. Muggleton, S.: Inverse entailment and Progol. New Generation Computing, Special issue on Inductive Logic Programming 13(3-4), 245-286 (1995)
8. Srinivasan, A.: The aleph manual (1999)
9. Dehaspe, L., Raedt, L.D.: Mining association rules in multiple relations. In: Džeroski, S., Lavrač, N. (eds.) ILP 1997. LNCS, vol. 1297, pp. 125-132. Springer, Heidelberg (1997)
10. Toprak, S.D., Senkul, P., Kavurucu, Y., Toroslu, I.H.: A new ILP-based concept discovery method for business intelligence. In: ICDE Workshop on Data Mining and Business Intelligence (April 2007)
11. Michalski, R., Larson, J.: Inductive inference of vl decision rules. In: Workshop on Pattern-Directed Inference Systems, Hawaii, SIGART Newsletter, vol. 63, pp. 33-44. ACM Press, New York (1997)
12. Hinton, G.: UCI machine learning repository kinship data set (1990), http://archive.ics.uci.edu/ml/datasets/Kinship