{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T20:06:52Z","timestamp":1743019612573,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319452456"},{"type":"electronic","value":"9783319452463"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"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":[[2016]]},"DOI":"10.1007\/978-3-319-45246-3_37","type":"book-chapter","created":{"date-parts":[[2016,11,29]],"date-time":"2016-11-29T16:55:13Z","timestamp":1480438513000},"page":"387-396","source":"Crossref","is-referenced-by-count":1,"title":["A Graph-Path Counting Approach for Learning Head Output Connected Relations"],"prefix":"10.1007","author":[{"given":"Nuran","family":"Peker","sequence":"first","affiliation":[]},{"given":"Alev","family":"Mutlu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,9,20]]},"reference":[{"issue":"1","key":"37_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/959242.959245","volume":"5","author":"S Dzeroski","year":"2003","unstructured":"Dzeroski, S.: Multi-relational data mining: an introduction. SIGKDD Explor. 5(1), 1\u201316 (2003)","journal-title":"SIGKDD Explor."},{"issue":"4","key":"37_CR2","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/BF03037089","volume":"8","author":"S Muggleton","year":"1991","unstructured":"Muggleton, S.: Inductive logic programming. New Gener. Comput. 8(4), 295\u2013318 (1991)","journal-title":"New Gener. Comput."},{"issue":"11","key":"37_CR3","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1145\/219717.219771","volume":"38","author":"I Bratko","year":"1995","unstructured":"Bratko, I., Muggleton, S.: Applications of inductive logic programming. Communications of the ACM 38(11), 65\u201370 (1995)","journal-title":"Communications of the ACM"},{"key":"37_CR4","unstructured":"Richards, B.L., Mooney, R.J.: Learning relations by pathfinding. In: Proceedings of the 10th National Conference on Artificial Intelligence, San Jose, CA, 12\u201316 July 1992, pp. 50\u201355 (1992)"},{"key":"37_CR5","doi-asserted-by":"crossref","unstructured":"Gao, Z., Zhang, Z., Huang, Z.: Extensions to the relational paths based learning approach RPBL. In: First Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009, Dong hoi, Quang binh, Vietnam, 1\u20133 April 2009, pp. 214\u2013219 (2009)","DOI":"10.1109\/ACIIDS.2009.40"},{"key":"37_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/978-3-319-22729-0_30","volume-title":"Big Data Analytics and Knowledge Discovery","author":"NC Abay","year":"2015","unstructured":"Abay, N.C., Mutlu, A., Karagoz, P.: A graph-based concept discovery method for n-Ary relations. In: Madria, S., Hara, T. (eds.) DaWaK 2015. LNCS, vol. 9263, pp. 391\u2013402. Springer, Heidelberg (2015)"},{"key":"37_CR7","unstructured":"Gonzalez, J., Holder, L., Cook, D.J.: Application of graph-based concept learning to the predictive toxicology domain. In: Proceedings of the Predictive Toxicology Challenge Workshop (2001)"},{"key":"37_CR8","unstructured":"Yan, X., Han, J.: gSpan: Graph-based substructure pattern mining. In: Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), 9\u201312 December 2002, Maebashi City, Japan, pp. 721\u2013724 (2002)"},{"issue":"3","key":"37_CR9","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/BF00872095","volume":"4","author":"K Yoshida","year":"1994","unstructured":"Yoshida, K., Motoda, H., Indurkhya, N.: Graph-based induction as a unified learning framework. Appl. Intell. 4(3), 297\u2013316 (1994)","journal-title":"Appl. Intell."},{"key":"37_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/3-540-45372-5_2","volume-title":"Principles of Data Mining and Knowledge Discovery","author":"A Inokuchi","year":"2000","unstructured":"Inokuchi, A., Washio, T., Motoda, H.: An apriori-based algorithm for mining frequent substructures from graph data. In: Zighed, D.A., Komorowski, J., \u017bytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 13\u201323. Springer, Heidelberg (2000)"},{"key":"37_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1007\/978-3-642-04686-5_13","volume-title":"Progress in Artificial Intelligence","author":"JCA Santos","year":"2009","unstructured":"Santos, J.C.A., Tamaddoni-Nezhad, A., Muggleton, S.: An ILP system for learning head output connected predicates. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds.) EPIA 2009. LNCS, vol. 5816, pp. 150\u2013159. Springer, Heidelberg (2009)"},{"key":"37_CR12","unstructured":"Hinton, G.: UCI machine learning repository (1990)"},{"issue":"8","key":"37_CR13","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1016\/j.knosys.2010.04.011","volume":"23","author":"Y Kavurucu","year":"2010","unstructured":"Kavurucu, Y., Senkul, P., Toroslu, I.H.: Concept discovery on relational databases: new techniques for search space pruning and rule quality improvement. Knowl.-Based Syst. 23(8), 743\u2013756 (2010)","journal-title":"Knowl.-Based Syst."},{"key":"37_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1007\/978-3-642-40131-2_29","volume-title":"Data Warehousing and Knowledge Discovery","author":"A Mutlu","year":"2013","unstructured":"Mutlu, A., Karagoz, P.: A hybrid graph-based method for concept rule discovery. In: Bellatreche, L., Mohania, M.K. (eds.) DaWaK 2013. LNCS, vol. 8057, pp. 327\u2013338. Springer, Heidelberg (2013)"}],"container-title":["Lecture Notes in Computer Science","Computational Collective Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-45246-3_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,25]],"date-time":"2017-06-25T00:47:48Z","timestamp":1498351668000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-45246-3_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319452456","9783319452463"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-45246-3_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]}}}