{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T12:23:41Z","timestamp":1602246221098},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"URL":"http:\/\/www.springer.com\/tdm","start":{"date-parts":[[2008,8,6]],"date-time":"2008-08-06T00:00:00Z","timestamp":1217980800000},"delay-in-days":0,"content-version":"tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2008,10]]},"DOI":"10.1007\/s10994-008-5076-4","type":"journal-article","created":{"date-parts":[[2008,8,5]],"date-time":"2008-08-05T14:14:20Z","timestamp":1217945660000},"page":"55-85","source":"Crossref","is-referenced-by-count":10,"title":["Learning probabilistic logic models from probabilistic examples"],"prefix":"10.1007","volume":"73","author":[{"given":"Jianzhong","family":"Chen","sequence":"first","affiliation":[]},{"given":"Stephen","family":"Muggleton","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9","family":"Santos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2008,8,6]]},"reference":[{"key":"5076_CR1","author":"H. Alan","year":"2007","unstructured":"Alan, H. (2007). Interpretations of probability. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Winter 2007 edition). Stanford: Stanford University. http:\/\/plato.stanford.edu\/archives\/win2007\/entries\/probability-interpret .","volume-title":"The Stanford encyclopedia of philosophy (Winter 2007 edition)"},{"issue":"2","key":"5076_CR2","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/S0959-440X(03)00031-9","volume":"13","author":"E. Alm","year":"2003","unstructured":"Alm, E., & Arkin, A. P. (2003). Biological networks. Current Opinion in Structural Biology, 13(2), 193\u2013202.","journal-title":"Current Opinion in Structural Biology"},{"key":"5076_CR3","unstructured":"Angelopoulos, N., & Cussens, J. (2006). Parameter estimation software implementing the f(ailure) a(adjusted) m(aximasation) algorithm for slps. http:\/\/scibsfs.bch.ed.ac.uk\/~nicos\/sware\/slps\/pe\/ ."},{"key":"5076_CR4","unstructured":"Arvanitis, A., Muggleton, S., Chen, J., & Watanabe, H. (2006). Abduction with stochastic logic programs based on a possible worlds semantics. In Short paper proceedings of the 16th international conference on inductive logic programming, University of Corunna."},{"key":"5076_CR5","unstructured":"Costa, V. S., Damas, L., Reis, R., & Azevedo, R. (2006). Yap Prolog user\u2019s manual. http:\/\/www.ncc.up.pt\/~vsc\/Yap\/ ."},{"issue":"3","key":"5076_CR6","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1023\/A:1010924021315","volume":"44","author":"J. Cussens","year":"2001","unstructured":"Cussens, J. (2001). Parameter estimation in stochastic logic programs. Machine Learning, 44(3), 245\u2013271.","journal-title":"Machine Learning"},{"key":"5076_CR7","author":"J. Cussens","first-page":"269","year":"2007","unstructured":"Cussens, J. (2007). Logic-based formalisms for statistical relational learning. In L. Getoor & B. Taskar (Eds.), Introduction to statistical relational learning (pp. 269\u2013290). Cambridge: MIT Press.","volume-title":"Introduction to statistical relational learning"},{"issue":"1","key":"5076_CR8","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1145\/959242.959247","volume":"5","author":"L. Raedt De","year":"2003","unstructured":"De Raedt, L., & Kersting, K. (2003). Probabilistic logic learning. ACM-SIGKDD Explorations: Special issue on Multi-Relational Data Mining, 5(1), 31\u201348.","journal-title":"ACM-SIGKDD Explorations: Special issue on Multi-Relational Data Mining"},{"key":"5076_CR9","author":"L. Raedt De","year":"2004","unstructured":"De Raedt, L., & Kersting, K. (2004). Probabilistic inductive logic programming. In S. Ben-David, J. Case, & A. Maruoka (Eds.), Lecture notes in computer science: Vol. 3244. Proceedings of the 15th international conference on algorithmic learning theory. Berlin: Springer.","series-title":"Lecture notes in computer science","volume-title":"Proceedings of the 15th international conference on algorithmic learning theory"},{"key":"5076_CR10","author":"L. Raedt De","year":"2008","unstructured":"De Raedt, L., Frasconi, P., Kersting, K., & Muggleton, S. (2008). In Lecture notes in computer science: Vol.\u00a04911. Probabilistic inductive logic programming\u2014theory and applications. Berlin: Springer.","series-title":"Lecture notes in computer science","volume-title":"Probabilistic inductive logic programming\u2014theory and applications","DOI":"10.1007\/978-3-540-78652-8","doi-asserted-by":"crossref"},{"key":"5076_CR11","author":"P. Flach","year":"2000","unstructured":"Flach, P., & Kakas, A. (2000). Pure and applied logic. Abductive and inductive reasoning. Dordrecht: Kluwer.","series-title":"Pure and applied logic","volume-title":"Abductive and inductive reasoning","DOI":"10.1007\/978-94-017-0606-3","doi-asserted-by":"crossref"},{"key":"5076_CR12","author":"N. Friedman","first-page":"129","year":"1998","unstructured":"Friedman, N. (1998). The Bayesian structural em algorithm. In G. Cooper & S. Moral (Eds.), Proceedings of the fourteenth annual conference on uncertainty in artificial intelligence (UAI-98) (pp. 129\u2013138). Madison: Morgan Kaufmann.","volume-title":"Proceedings of the fourteenth annual conference on uncertainty in artificial intelligence (UAI-98)"},{"key":"5076_CR13","author":"L. Getoor","year":"2007","unstructured":"Getoor, L., & Taskar, B. (2007). Adaptive computation and machine learning. Introduction to statistical relational learning. Cambridge: MIT Press.","series-title":"Adaptive computation and machine learning","volume-title":"Introduction to statistical relational learning","DOI":"10.7551\/mitpress\/7432.001.0001","doi-asserted-by":"crossref"},{"key":"5076_CR14","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/0004-3702(90)90019-V","volume":"46","author":"J. Y. Halpern","year":"1989","unstructured":"Halpern, J. Y. (1989). An analysis of first-order logics of probability. Artificial Intelligence, 46, 311\u2013350.","journal-title":"Artificial Intelligence"},{"key":"5076_CR15","unstructured":"Haussler, D. (1990). Probably approximately correct learning. In National conference on artificial intelligence (pp.\u00a01101\u20131108)."},{"key":"5076_CR16","series-title":"Lecture notes in artificial intelligence","first-page":"402","volume-title":"Computational logic: logic programming and beyond, part\u00a0I","author":"A. Kakas","year":"2002","unstructured":"Kakas, A., & Denecker, M. (2002). Abduction in logic programming. In A. Kakas & F. Sadri (Eds.), Lecture notes in artificial intelligence: Vol. 2407. Computational logic: logic programming and beyond, part\u00a0I (pp. 402\u2013436). Berlin: Springer."},{"issue":"6","key":"5076_CR17","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1093\/logcom\/2.6.719","volume":"2","author":"A. C. Kakas","year":"1992","unstructured":"Kakas, A. C., Kowalski, R. A., & Toni, F. (1992). Abductive logic programming. Journal of Logic and Computation, 2(6), 719\u2013770.","journal-title":"Journal of Logic and Computation"},{"key":"5076_CR18","unstructured":"Kersting, K., & De Raedt, L. (2000). Bayesian logic programs. In Proceedings of the work-in-progress track at the 10th international conference on inductive logic programming (pp.\u00a0138\u2013155)."},{"issue":"1\u20132","key":"5076_CR19","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/S0169-7439(98)00167-1","volume":"44","author":"H. A. Martensa","year":"1998","unstructured":"Martensa, H. A., & Dardenne, P. (1998). Validation and verification of regression in small data sets. Chemometrics and Intelligent Laboratory Systems, 44(1\u20132), 99\u2013121.","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"key":"5076_CR20","unstructured":"MetaLog Project. (2004\u20132006). http:\/\/www.doc.ic.ac.uk\/bioinformatics\/metalog ."},{"key":"5076_CR21","author":"S. Muggleton","first-page":"254","year":"1996","unstructured":"Muggleton, S. (1996). Stochastic logic programs. In L. De Raedt (Ed.), Advances in inductive logic programming (pp. 254\u2013264). Amsterdam: IOS Press.","volume-title":"Advances in inductive logic programming"},{"key":"5076_CR22","author":"S. Muggleton","year":"2000","unstructured":"Muggleton, S. (2000). Learning stochastic logic programs. In L. Getoor & D. Jensen (Eds.), Proceedings of the AAAI2000 workshop on learning statistical models from relational data. Menlo Park: AAAI.","volume-title":"Proceedings of the AAAI2000 workshop on learning statistical models from relational data"},{"key":"5076_CR23","unstructured":"Muggleton, S. (2002a). Learning structure and parameters of stochastic logic programs. Electronic Transactions in Artificial Intelligence, 6.","DOI":"10.1007\/3-540-36468-4_13","doi-asserted-by":"crossref"},{"key":"5076_CR24","unstructured":"Muggleton, S. (2002b). Progol version 5.0. http:\/\/www.doc.ic.ac.uk\/~shm\/Software\/progol5.0\/ ."},{"key":"5076_CR25","author":"S. Muggleton","first-page":"130","year":"2000","unstructured":"Muggleton, S., & Bryant, C. (2000). Theory completion using inverse entailment. In Proceedings of the 10th international workshop on inductive logic programming (ILP-00) (pp. 130\u2013146). Berlin: Springer.","volume-title":"Proceedings of the 10th international workshop on inductive logic programming (ILP-00)","DOI":"10.1007\/3-540-44960-4_8","doi-asserted-by":"crossref"},{"key":"5076_CR26","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1016\/0743-1066(94)90035-3","volume":"19\u201320","author":"S. Muggleton","year":"1994","unstructured":"Muggleton, S., & De Raedt, L. (1994). Inductive logic programming: theory and methods. Journal of Logic Programming, 19\u201320, 629\u2013679.","journal-title":"Journal of Logic Programming"},{"key":"5076_CR27","author":"J. Pearl","year":"1988","unstructured":"Pearl, J. (1988). Probabilistic reasoning in intelligent systems: networks of plausible inference. Los Altos: Morgan Kaufmann.","volume-title":"Probabilistic reasoning in intelligent systems: networks of plausible inference"},{"issue":"1","key":"5076_CR28","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/0004-3702(93)90061-F","volume":"64","author":"D. Poole","year":"1993","unstructured":"Poole, D. (1993). Probabilistic Horn abduction and Bayesian networks. Artificial Intelligence, 64(1), 81\u2013129.","journal-title":"Artificial Intelligence"},{"issue":"1\u20132","key":"5076_CR29","first-page":"5","volume":"94","author":"D. Poole","year":"1997","unstructured":"Poole, D. (1997). The independent choice logic for modelling multiple agents under uncertainty. Artificial Intelligence, 94(1\u20132), 5\u201356.","journal-title":"Artificial Intelligence"},{"key":"5076_CR30","unstructured":"Puech, A., & Muggleton, S. (2003). A\u00a0comparison of stochastic logic programs and Bayesian logic programs. In IJCAI03 workshop on learning statistical models from relational data. IJCAI."},{"issue":"1\u20132","key":"5076_CR31","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s10994-006-5833-1","volume":"62","author":"M. Richardson","year":"2006","unstructured":"Richardson, M., & Domingos, P. (2006). Markov logic networks. Machine Learning, 62(1\u20132), 107\u2013136.","journal-title":"Machine Learning"},{"key":"5076_CR32","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1214\/aos\/1176346150","volume":"11","author":"J. Rissanen","year":"1982","unstructured":"Rissanen, J. (1982). A universal prior for integers and estimation by minimum description length. Annals of Statistics, 11, 416\u2013431.","journal-title":"Annals of Statistics"},{"key":"5076_CR33","unstructured":"Sato, T. (1995). A\u00a0statistical learning method for logic programs with distribution semantics. In Proceedings of the 12th international conference on logic programming (ICLP-1995) (pp.\u00a0715\u2013729)."},{"key":"5076_CR34","unstructured":"Sato, T., Zhou, N.-F., Kameya, Y., & Izumi, Y. (2008). Prism user\u2019s manual (version 1.11.2). http:\/\/sato-www.cs.titech.ac.jp\/prism\/ ."},{"key":"5076_CR35","unstructured":"Stefan, W., & Steven, C. (2004). Finite mathematics and applied calculus (3rd ed.). Brooks\/Cole."},{"key":"5076_CR36","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s10994-006-8988-x","volume":"64","author":"A. Tamaddoni-Nezhad","year":"2006","unstructured":"Tamaddoni-Nezhad, A., Chaleil, R., Kakas, A., & Muggleton, S. (2006). Application of abductive ILP to learning metabolic network inhibition from temporal data. Machine Learning, 64, 209\u2013230. doi: 10.1007\/s10994-006-8988-x .","journal-title":"Machine Learning"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-008-5076-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-008-5076-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-008-5076-4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,7]],"date-time":"2020-05-07T13:03:20Z","timestamp":1588856600000},"score":1.0,"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,8,6]]},"references-count":36,"journal-issue":{"published-print":{"date-parts":[[2008,10]]},"issue":"1"},"alternative-id":["5076"],"URL":"http:\/\/dx.doi.org\/10.1007\/s10994-008-5076-4","relation":{"cites":[]},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":["Software","Artificial Intelligence"]}}