{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T21:45:54Z","timestamp":1725745554757},"publisher-location":"Berlin, Heidelberg","reference-count":18,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642401305"},{"type":"electronic","value":"9783642401312"}],"license":[{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-40131-2_19","type":"book-chapter","created":{"date-parts":[[2013,8,21]],"date-time":"2013-08-21T03:53:22Z","timestamp":1377057202000},"page":"222-235","source":"Crossref","is-referenced-by-count":1,"title":["Fast Causal Network Inference over Event Streams"],"prefix":"10.1007","author":[{"given":"Saurav","family":"Acharya","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Byung Suk","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"19_CR1","unstructured":"Heckerman, D.: A Bayesian approach to learning causal networks. In: UAI, pp. 285\u2013295 (1995)"},{"issue":"482","key":"19_CR2","doi-asserted-by":"publisher","first-page":"778","DOI":"10.1198\/016214508000000193","volume":"103","author":"B. Ellis","year":"2008","unstructured":"Ellis, B., Wong, W.H.: Learning causal Bayesian network structures from experimental data. J. American Statistics Association\u00a0103(482), 778\u2013789 (2008)","journal-title":"J. American Statistics Association"},{"key":"19_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1007\/978-3-642-01307-2_28","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"G. Li","year":"2009","unstructured":"Li, G., Leong, T.-Y.: Active learning for causal Bayesian network structure with non-symmetrical entropy. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, T.-B. (eds.) PAKDD 2009. LNCS, vol.\u00a05476, pp. 290\u2013301. Springer, Heidelberg (2009)"},{"key":"19_CR4","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1007\/11681960_8","volume-title":"Modeling Decisions for Artificial Intelligence","author":"S. Meganck","year":"2006","unstructured":"Meganck, S., Leray, P., Manderick, B.: Learning causal Bayesian networks from observations and experiments: a decision theoretic approach. In: Torra, V., Narukawa, Y., Valls, A., Domingo-Ferrer, J. (eds.) MDAI 2006. LNCS (LNAI), vol.\u00a03885, pp. 58\u201369. Springer, Heidelberg (2006)"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Pearl, J.: Causality: Models, Reasoning and Inference, 2nd edn. Cambridge University Press (2009)","DOI":"10.1017\/CBO9780511803161"},{"key":"19_CR6","unstructured":"Spirtes, P., Glymour, C.N., Scheines, R.: Causality from probability. In: ACSS (1990)"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Spirtes, P., Glymour, C., Scheines, R.: Causation, Prediction, and Search. MIT Press (2000)","DOI":"10.7551\/mitpress\/1754.001.0001"},{"issue":"1-2","key":"19_CR8","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/S0004-3702(02)00191-1","volume":"137","author":"J. Cheng","year":"2002","unstructured":"Cheng, J., Greiner, R., Kelly, J., Bell, D., Liu, W.: Learning Bayesian networks from data: an information-theory based approach. Artificial Intelligence\u00a0137(1-2), 43\u201390 (2002)","journal-title":"Artificial Intelligence"},{"key":"19_CR9","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1093\/biomet\/82.4.669","volume":"82","author":"J. Pearl","year":"1995","unstructured":"Pearl, J.: Causal diagrams for empirical research. Biometrika\u00a082, 669\u2013688 (1995)","journal-title":"Biometrika"},{"key":"19_CR10","unstructured":"Popper, K.: The Logic of Scientific Discovery, Reprint edn. Routledge (October 1992)"},{"key":"19_CR11","first-page":"445","volume":"2","author":"D.M. Chickering","year":"2002","unstructured":"Chickering, D.M.: Learning equivalence classes of Bayesian-network structures. J. Machine Learning Research\u00a02, 445\u2013498 (2002)","journal-title":"J. Machine Learning Research"},{"key":"19_CR12","first-page":"2149","volume":"7","author":"L.M. Campos de","year":"2006","unstructured":"de Campos, L.M.: A scoring function for learning Bayesian networks based on mutual information and conditional independence tests. J. Machine Learning Research\u00a07, 2149\u20132187 (2006)","journal-title":"J. Machine Learning Research"},{"key":"19_CR13","unstructured":"Bishop, Y.M., Fienberg, S.E., Holland, P.W.: Discrete Multivariate Analysis: Theory and Practice. MIT Press (1975)"},{"key":"19_CR14","unstructured":"Kullback, S.: Information Theory and Statistics, 2nd edn. Dover Publication (1968)"},{"key":"19_CR15","unstructured":"Spirtes, P., Meek, C.: Learning Bayesian networks with discrete variables from data. In: KDD, pp. 294\u2013299 (1995)"},{"key":"19_CR16","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1177\/0049124198027002004","volume":"27","author":"J. Pearl","year":"1998","unstructured":"Pearl, J.: Graphs, causality, and structural equation models. Sociological Methods and Research\u00a027, 226\u2013284 (1998)","journal-title":"Sociological Methods and Research"},{"issue":"1","key":"19_CR17","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/s10994-006-6889-7","volume":"65","author":"I. Tsamardinos","year":"2006","unstructured":"Tsamardinos, I., Brown, L.E., Aliferis, C.F.: The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn.\u00a065(1), 31\u201378 (2006)","journal-title":"Mach. Learn."},{"key":"19_CR18","unstructured":"Frank, A., Asuncion, A.: UCI machine learning repository (2010)"}],"container-title":["Lecture Notes in Computer Science","Data Warehousing and Knowledge Discovery"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-40131-2_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,16]],"date-time":"2019-05-16T18:50:06Z","timestamp":1558032606000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-40131-2_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642401305","9783642401312"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-40131-2_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2013]]}}}