{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:52:46Z","timestamp":1740099166758,"version":"3.37.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030041908"},{"type":"electronic","value":"9783030041915"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-04191-5_22","type":"book-chapter","created":{"date-parts":[[2018,11,15]],"date-time":"2018-11-15T07:12:31Z","timestamp":1542265951000},"page":"237-249","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Rule-Mining and Clustering in Business Process Analysis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3573-6742","authenticated-orcid":false,"given":"Paul N.","family":"Taylor","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephanie","family":"Kiss","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,16]]},"reference":[{"issue":"9","key":"22_CR1","doi-asserted-by":"publisher","first-page":"1128","DOI":"10.1109\/TKDE.2004.47","volume":"16","author":"W Aalst Van der","year":"2004","unstructured":"Van der Aalst, W., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128\u20131142 (2004)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"22_CR2","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Imieli\u0144ski, T., Swami, A.: Mining association rules between sets of items in large databases. In: ACM SIGMOD Record, vol. 22, pp. 207\u2013216. ACM (1993)","DOI":"10.1145\/170036.170072"},{"key":"22_CR3","unstructured":"Agrawal, R., Srikant, R., et al.: Fast algorithms for mining association rules. In: Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, vol. 1215, pp. 487\u2013499 (1994)"},{"key":"22_CR4","unstructured":"Ayg\u00fcn, E.: Python-Alignment, May 2017. https:\/\/github.com\/eseraygun\/python-alignment"},{"issue":"1","key":"22_CR5","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1108\/09574090310806512","volume":"14","author":"KL Croxton","year":"2003","unstructured":"Croxton, K.L.: The order fulfillment process. Int. J. Logist. Manag. 14(1), 19\u201332 (2003)","journal-title":"Int. J. Logist. Manag."},{"key":"22_CR6","unstructured":"Gabadinho, A., Ritschard, G., Studer, M., M\u00fcller, N.S.: Mining sequence data in R with the TraMineR package: a users guide for version 1.2. University of Geneva, Geneva (2009)"},{"key":"22_CR7","doi-asserted-by":"crossref","unstructured":"Grygorash, O., Zhou, Y., Jorgensen, Z.: Minimum spanning tree based clustering algorithms. In: 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2006), pp. 73\u201381 (2006)","DOI":"10.1109\/ICTAI.2006.83"},{"key":"22_CR8","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1007\/978-3-642-14274-1_29","volume-title":"Case-Based Reasoning. Research and Development","author":"S Kapetanakis","year":"2010","unstructured":"Kapetanakis, S., Petridis, M., Knight, B., Ma, J., Bacon, L.: A case based reasoning approach for the monitoring of business workflows. In: Bichindaritz, I., Montani, S. (eds.) ICCBR 2010. LNCS (LNAI), vol. 6176, pp. 390\u2013405. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-14274-1_29"},{"issue":"1","key":"22_CR9","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1090\/S0002-9939-1956-0078686-7","volume":"7","author":"JB Kruskal","year":"1956","unstructured":"Kruskal, J.B.: On the shortest spanning subtree of a graph and the traveling salesman problem. Proc. Am. Math. Soc. 7(1), 48\u201350 (1956)","journal-title":"Proc. Am. Math. Soc."},{"key":"22_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1007\/978-3-642-14274-1_31","volume-title":"Case-Based Reasoning. Research and Development","author":"M Minor","year":"2010","unstructured":"Minor, M., Bergmann, R., G\u00f6rg, S., Walter, K.: Towards case-based adaptation of workflows. In: Bichindaritz, I., Montani, S. (eds.) ICCBR 2010. LNCS (LNAI), vol. 6176, pp. 421\u2013435. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-14274-1_31"},{"issue":"3","key":"22_CR11","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/0022-2836(70)90057-4","volume":"48","author":"SB Needleman","year":"1970","unstructured":"Needleman, S.B., Wunsch, C.D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48(3), 443\u2013453 (1970)","journal-title":"J. Mol. Biol."},{"key":"22_CR12","unstructured":"Ritschard, G., B\u00fcrgin, R., Studer, M.: Exploratory mining of life event histories. In: Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences, pp. 221\u2013253 (2013)"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence XXXV"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04191-5_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,2]],"date-time":"2019-11-02T08:20:02Z","timestamp":1572682802000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-04191-5_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030041908","9783030041915"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04191-5_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"SGAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Innovative Techniques and Applications of Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambridge","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"38","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sgai2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.bcs-sgai.org\/ai2018\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}