{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T09:36:18Z","timestamp":1743154578850,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319083889"},{"type":"electronic","value":"9783319083896"}],"license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-08389-6_3","type":"book-chapter","created":{"date-parts":[[2014,7,17]],"date-time":"2014-07-17T10:43:39Z","timestamp":1405593819000},"page":"25-30","source":"Crossref","is-referenced-by-count":1,"title":["Towards a Framework for Learning from Networked Data"],"prefix":"10.1007","author":[{"given":"Jan","family":"Ramon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"issue":"5939","key":"3_CR1","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1126\/science.1173299","volume":"325","author":"A.L. Barab\u00e1si","year":"2009","unstructured":"Barab\u00e1si, A.L.: Scale-free networks: A decade and beyond. Science\u00a0325(5939), 412\u2013413 (2009)","journal-title":"Science"},{"key":"3_CR2","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1007\/s10618-011-0217-y","volume":"23","author":"T. Calders","year":"2011","unstructured":"Calders, T., Ramon, J., Van Dyck, D.: All normalized anti-monotonic overlap graph measures are bounded. Data Mining and Knowledge Discovery\u00a023, 503\u2013548 (2011)","journal-title":"Data Mining and Knowledge Discovery"},{"key":"3_CR3","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/S0004-3702(97)00041-6","volume":"95","author":"L. De Raedt","year":"1997","unstructured":"De Raedt, L.: Logical settings for concept learning. Artificial Intelligence\u00a095, 187\u2013201 (1997)","journal-title":"Artificial Intelligence"},{"key":"3_CR4","series-title":"LNAI","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BFb0027304","volume-title":"Inductive Logic Programming","author":"L. De Raedt","year":"1998","unstructured":"De Raedt, L.: Attribute-value learning versus inductive logic programming: The missing links (extended abstract). In: Page, D. (ed.) ILP 1998. LNCS (LNAI), vol.\u00a01446, pp. 1\u20138. Springer, Heidelberg (1998)"},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"2253","DOI":"10.1021\/pr4001114","volume":"12","author":"T. Fannes","year":"2013","unstructured":"Fannes, T., Vandermarliere, E., Schietgat, L., Degroeve, S., Martens, L., Ramon, J.: Predicting tryptic cleavage from proteomics data using decision tree ensembles. Journal of Proteome Research\u00a012, 2253\u20132259 (2013)","journal-title":"Journal of Proteome Research"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Getoor, L., Taskar, B.: An Introduction to Statistical Relational Learning. MIT Press (2007)","DOI":"10.7551\/mitpress\/7432.001.0001"},{"issue":"3","key":"3_CR7","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1007\/s10618-009-0162-1","volume":"21","author":"T. Horv\u00e1th","year":"2010","unstructured":"Horv\u00e1th, T., Ramon, J., Wrobel, S.: Frequent subgraph mining in outerplanar graphs. Knowledge Discovery and Data Mining\u00a021(3), 472\u2013508 (2010)","journal-title":"Knowledge Discovery and Data Mining"},{"key":"3_CR8","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1007\/s10618-013-0321-2","volume":"27","author":"A. Kibriya","year":"2013","unstructured":"Kibriya, A., Ramon, J.: Nearly exact mining of frequent trees in large networks. Data Mining and Knowledge Discovery\u00a027, 478\u2013504 (2013)","journal-title":"Data Mining and Knowledge Discovery"},{"key":"3_CR9","unstructured":"Martens, L., Laukens, K., Ramon, J., Valkenborg, D.: Inspector: An integrated informatics platform for mass-spectrometry protein assays"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Newman, M.: Networks: An introduction. Oxford University Press (2010)","DOI":"10.1093\/acprof:oso\/9780199206650.003.0001"},{"key":"3_CR11","series-title":"LNAI","doi-asserted-by":"crossref","DOI":"10.1007\/3-540-62927-0","volume-title":"Foundations of Inductive Logic Programming","author":"S.-H. Nienhuys-Cheng","year":"1997","unstructured":"Nienhuys-Cheng, S.-H., de Wolf, R.: Foundations of Inductive Logic Programming. LNCS (LNAI), vol.\u00a01228. Springer, Heidelberg (1997)"},{"key":"3_CR12","unstructured":"Wang, Y., Ramon, J., Guo, Z.-C.: Learning from networked examples in a k-partite graph. In: Proceedings of la Confrence sur l\u2019Apprentissage Automatique, Lille, France, pp. 1\u20138 (July 2013)"}],"container-title":["Lecture Notes in Computer Science","Graph-Based Representation and Reasoning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-08389-6_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T05:25:15Z","timestamp":1676870715000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-08389-6_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319083889","9783319083896"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-08389-6_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2014]]}}}