메뉴 건너뛰기




Volumn 83, Issue 2, 2011, Pages 163-192

Block-wise construction of tree-like relational features with monotone reducibility and redundancy

Author keywords

Inductive logic programming; Propositionalization; Relational machine learning

Indexed keywords

CLASSIFICATION LEARNING; FIRST-ORDER; INDUCTIVE LOGIC; MONOTONICITY; PROPOSITIONALIZATION; RELATIONAL FEATURES; RELATIONAL MACHINE LEARNING; STATE OF THE ART;

EID: 79958793910     PISSN: 08856125     EISSN: 15730565     Source Type: Journal    
DOI: 10.1007/s10994-010-5208-5     Document Type: Conference Paper
Times cited : (30)

References (34)
  • 6
    • 0003323974 scopus 로고
    • The application of inductive logic programming to finite element mesh design
    • San Diego: Academic Press
    • Dolsak, B., & Muggleton, S. (1992). The application of inductive logic programming to finite element mesh design. In Inductive logic programming (pp. 453-472). San Diego: Academic Press.
    • (1992) Inductive Logic Programming , pp. 453-472
    • Dolsak, B.1    Muggleton, S.2
  • 7
    • 0020781665 scopus 로고
    • Degrees of acyclicity for hypergraphs and relational database schemes
    • DOI 10.1145/2402.322390
    • Fagin, R. (1983). Degrees of acyclicity for hypergraphs and relational database schemes. Journal of the Association for Computing Machinery, 30(3), 514-550. (Pubitemid 13573333)
    • (1983) Journal of the ACM , vol.30 , Issue.3 , pp. 514-550
    • Fagin, R.1
  • 9
    • 0035113097 scopus 로고    scopus 로고
    • The predictive toxicology challenge 2000-2001
    • Helma, C., King, R. D., Kramer, S., & Srinivasan, A. (2001). The predictive toxicology challenge 2000-2001. Bioinformatics, 17(1), 107-108. (Pubitemid 32178021)
    • (2001) Bioinformatics , vol.17 , Issue.1 , pp. 107-108
    • Helma, C.1    King, R.D.2    Kramer, S.3    Srinivasan, A.4
  • 12
    • 84937420049 scopus 로고    scopus 로고
    • Transformation-Based Learning Using Multirelational Aggregation
    • Krogel, M. A., & Wrobel, S. (2001). Transformation-based learning using multirelational aggregation. In ILP '01: proceedings of the 11th international conference on inductive logic programming (pp. 142-155). Berlin: Springer. (Pubitemid 33332604)
    • (2001) Lecture Notes in Computer Science , Issue.2157 , pp. 142-155
    • Krogel, M.-A.1    Wrobel, S.2
  • 14
    • 71149091036 scopus 로고    scopus 로고
    • Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties
    • Kuželka, O., & Železný, F. (2009). Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties. In ICML 2009: the 26th int. conf. on machine learning.
    • (2009) ICML 2009: The 26th Int. Conf. on Machine Learning
    • Kuželka, O.1    Železný, F.2
  • 15
    • 33750734364 scopus 로고    scopus 로고
    • KFOIL: Learning simple relational kernels
    • Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
    • Landwehr, N., Passerini, A., De Raedt, L., & Frasconi, P. (2006). kFOIL: learning simple relational kernels. In AAAI'06: proceedings of the 21st national conference on artificial intelligence (pp. 389-394). Menlo Park: AAAI Press. (Pubitemid 44705315)
    • (2006) Proceedings of the National Conference on Artificial Intelligence , vol.1 , pp. 389-394
    • Landwehr, N.1    Passerini, A.2    De Raedt, L.3    Frasconi, P.4
  • 17
    • 85008021624 scopus 로고    scopus 로고
    • An extended transformation approach to inductive logic programming
    • Lavrač, N., & Flach, P. A. (2001). An extended transformation approach to inductive logic programming. ACM Transactions on Computational Logic, 2(4), 458-494.
    • (2001) ACM Transactions on Computational Logic , vol.2 , Issue.4 , pp. 458-494
    • Lavrač, N.1    Flach, P.A.2
  • 18
    • 0032648857 scopus 로고    scopus 로고
    • A study of relevance for learning in deductive databases
    • Lavrač, N., Gamberger, D., & Jovanoski, V. (1999). A study of relevance for learning in deductive databases. Journal of Logic Programming, 40(2/3), 215-249.
    • (1999) Journal of Logic Programming , vol.40 , Issue.2-3 , pp. 215-249
    • Lavrač, N.1    Gamberger, D.2    Jovanoski, V.3
  • 22
    • 14944375202 scopus 로고    scopus 로고
    • The Gaston tool for frequent subgraph mining
    • DOI 10.1016/j.entcs.2004.12.039, PII S1571066105001064, Proceedings of the International Workshop on Graph-Based Tools (GraBaTs 2004)
    • Nijssen, S., & Kok, J. N. (2005). The Gaston tool for frequent subgraph mining. Electronic Notes in Theoretical Computer Science, 127(1), 77-87. (Pubitemid 40371095)
    • (2005) Electronic Notes in Theoretical Computer Science , vol.127 , Issue.1 , pp. 77-87
    • Nijssen, S.1    Kok, J.N.2
  • 23
    • 1942452297 scopus 로고    scopus 로고
    • Online feature selection using grafting
    • Menlo Park: AAAI Press
    • Perkins, S., & Theiler, J. (2003). Online feature selection using grafting. In ICML (pp. 592-599).Menlo Park: AAAI Press.
    • (2003) ICML , pp. 592-599
    • Perkins, S.1    Theiler, J.2
  • 24
    • 0001172265 scopus 로고
    • Learning logical definitions from relations
    • Quinlan, J. R. (1990). Learning logical definitions from relations. Machine Learning, 5(3), 239-266.
    • (1990) Machine Learning , vol.5 , Issue.3 , pp. 239-266
    • Quinlan, J.R.1
  • 26
    • 84957891317 scopus 로고    scopus 로고
    • Carcinogenesis Predictions Using ILP
    • Inductive Logic Programming
    • Srinivasan, A., King, R. D., Muggleton, S., & Sternberg, M. J. E. (1997). Carcinogenesis predictions using ILP. In ILP '97: proceedings of the 7th international workshop on inductive logic programming (pp. 273-287). Berlin: Springer. (Pubitemid 127124399)
    • (1997) Lecture Notes in Computer Science , Issue.1297 , pp. 273-287
    • Srinivasan, A.1    King, R.D.2    Muggleton, S.H.3    Sternberg, M.J.E.4
  • 27
    • 26944486424 scopus 로고    scopus 로고
    • Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity
    • Swamidass, S. J., Chen, J., Bruand, J., Phung, P., Ralaivola, L.,& Baldi, P. (2005). Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity. Bioinformatics, 21(1), 359-368.
    • (2005) Bioinformatics , vol.21 , Issue.1 , pp. 359-368
    • Swamidass, S.J.1    Chen, J.2    Bruand, J.3    Phung, P.4    Ralaivola, L.5    Baldi, P.6
  • 30
    • 32144454875 scopus 로고    scopus 로고
    • Propositionalization-based relational subgroup discovery with RSD
    • DOI 10.1007/s10994-006-5834-0
    • Železný, F., & Lavrač, N. (2006). Propositionalization-based relational subgroup discovery with RSD. Machine Learning, 62, 33-63. (Pubitemid 43204506)
    • (2006) Machine Learning , vol.62 , Issue.SPEC. ISS. , pp. 33-63
    • Zelezny, F.1    Lavrac, N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.