Knowledge discovery from structured data by beam-wise graph-based induction

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

Volumn 2417, Issue , 2002, Pages 255-264

  Matsuda, Takashi ^a   Motoda, Hiroshi ^a   Yoshida, Tetsuya ^a   Washio, Takashi ^a  

^a OSAKA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; LEARNING SYSTEMS;

ATTRIBUTE-VALUE PAIRS; GRAPH STRUCTURES; GRAPH-BASED INDUCTION; MACHINE LEARNING TECHNIQUES; PREDICTIVE ACCURACY; SEARCH CAPABILITIES; STEPWISE PAIR EXPANSION; TYPICAL PATTERNS;

GRAPHIC METHODS;

EID: 84947447467     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45683-x_29     Document Type: Conference Paper

References (13)

1. C. L. Blake, E. Keogh, and C.J. Merz. Uci repository of machine leaning database, 1998. http://www.ics.uci.edu/∼mlearn/MLRepository.html.
2. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Wadsworth & Brooks/Cole Advanced Books & Software, 1984.
3. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. The cn2 induction algorithm. Machine Learning, 3:261–283, 1989.
4. D. J. Cook and L. B. Holder. Graph-based data mining. IEEE Intelligent Systems, 15(2):32–41, 2000.
5. S. Fortin. The graph isomorphism problem, 1996.
6. A. Inokuchi, T. Washio, and H. Motoda. An apriori-based algorithm for mining frequent substructures from graph data. In Proc. of the 4th European Conference on Principles of Data Mining and Knowledge Discovery, pages 13–23, 2000.
7. T. Matsuda, T. Horiuchi, H. Motoda, and T. Washio. Extension of graph-based induction for general graph structured data. In Knowledge Discovery and Data Mining: Current Issues and New Applications, Springer Verlag, LNAI 1805, pages 420–431, 2000.
8. R. S. Michalski. Learning flexible concepts: Fundamental ideas and a method based on two-tiered representaion. In Machine Learning, An Artificial Intelligence Approiach, 3:63–102, 1990.
9. S. Muggleton and L. de Raedt: Inductive logic programming: Theory and methods. Journal of Logic Programming, 19(20):629–679, 1994.
10. J. R. Quinlan. Induction of decision trees. Machine Learning, 1:81–106, 1986.
11. J. R. Quinlan. C4.5:Programs For Machine Learning. Morgan Kaufmann Publishers, 1993.
12. R. C. Read and D. G. Corneil. The graph isomorphism disease. Journal of Graph Theory, 1:339–363, 1977.
13. K. Yoshida and H. Motoda: Clip: Concept learning from inference pattern. Journal of Artificial Intelligence, 75(1):63–92, 1995.