{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T03:37:47Z","timestamp":1769225867307,"version":"3.49.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T00:00:00Z","timestamp":1579564800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T00:00:00Z","timestamp":1579564800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Data Min Knowl Disc"],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1007\/s10618-019-00672-w","type":"journal-article","created":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T14:03:41Z","timestamp":1579615421000},"page":"563-609","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["NegPSpan: efficient extraction of negative sequential patterns with embedding constraints"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4909-5843","authenticated-orcid":false,"given":"Thomas","family":"Guyet","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ren\u00e9","family":"Quiniou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,1,21]]},"reference":[{"issue":"3","key":"672_CR1","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1007\/s10618-017-0547-5","volume":"32","author":"G Bosc","year":"2018","unstructured":"Bosc G, Boulicaut JF, Ra\u00efssi C, Kaytoue M (2018) Anytime discovery of a diverse set of patterns with monte carlo tree search. Data Min Knowl Discov 32(3):604\u2013650","journal-title":"Data Min Knowl Discov"},{"issue":"6","key":"672_CR2","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/MIS.2015.105","volume":"30","author":"L Cao","year":"2015","unstructured":"Cao L, Yu PS, Kumar V (2015) Nonoccurring behavior analytics: a new area. Intell Syst 30(6):4\u201311","journal-title":"Intell Syst"},{"key":"672_CR3","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1016\/j.artint.2016.03.001","volume":"235","author":"L Cao","year":"2016","unstructured":"Cao L, Dong X, Zheng Z (2016) e-NSP: efficient negative sequential pattern mining. Artif Intell 235:156\u2013182","journal-title":"Artif Intell"},{"key":"672_CR4","doi-asserted-by":"crossref","unstructured":"Dauxais Y, Guyet T, Gross-Amblard D, Happe A (2017) Discriminant chronicles mining\u2014application to care pathways analytics. In: Proceedings of 16th conference on artificial intelligence in medicine (AIME), pp 234\u2013244","DOI":"10.1007\/978-3-319-59758-4_26"},{"key":"672_CR5","doi-asserted-by":"crossref","unstructured":"Dong X, Gong Y, Cao L (2018a) e-RNSP: an efficient method for mining repetition negative sequential patterns. IEEE Trans Cybern. https:\/\/doi.org\/10.1109\/TCYB.2018.2869907","DOI":"10.1109\/TCYB.2018.2869907"},{"key":"672_CR6","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.patcog.2018.06.016","volume":"84","author":"X Dong","year":"2018","unstructured":"Dong X, Gong Y, Cao L (2018b) F-NSP$$+$$: a fast negative sequential patterns mining method with self-adaptive data storage. Pattern Recognit 84:13\u201327","journal-title":"Pattern Recognit"},{"key":"672_CR7","doi-asserted-by":"crossref","unstructured":"Giannotti F, Nanni M, Pedreschi D (2006) Efficient mining of temporally annotated sequences. In: Proceedings of the SIAM international conference on data mining, pp 348\u2013359","DOI":"10.1137\/1.9781611972764.31"},{"issue":"02","key":"672_CR8","doi-asserted-by":"publisher","first-page":"1750002","DOI":"10.1142\/S0218001417500021","volume":"31","author":"Y Gong","year":"2017","unstructured":"Gong Y, Xu T, Dong X, Lv G (2017) e-NSPFI: efficient mining negative sequential pattern from both frequent and infrequent positive sequential patterns. Int J Pattern Recognit Artif Intell 31(02):1750002","journal-title":"Int J Pattern Recognit Artif Intell"},{"key":"672_CR9","doi-asserted-by":"crossref","unstructured":"Han J, Pei J, Mortazavi-Asl B, Chen Q, Dayal U, Hsu MC (2000) FreeSpan: frequent pattern-projected sequential pattern mining. In: Proceedings of the sixth international conference on knowledge discovery and data mining (SIGKDD), pp 355\u2013359","DOI":"10.1145\/347090.347167"},{"key":"672_CR10","doi-asserted-by":"crossref","unstructured":"Hsueh SC, Lin MY, Chen CL (2008) Mining negative sequential patterns for e-commerce recommendations. In: Proceedings of Asia-Pacific services computing conference, pp 1213\u20131218","DOI":"10.1109\/APSCC.2008.183"},{"issue":"3","key":"672_CR11","first-page":"115","volume":"5","author":"S Kamepalli","year":"2014","unstructured":"Kamepalli S, Sekhara R, Kurra R (2014) Frequent negative sequential patterns - a survey. Int J Comput Eng Technol 5(3):115\u2013121","journal-title":"Int J Comput Eng Technol"},{"key":"672_CR12","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.knosys.2016.08.022","volume":"111","author":"JCW Lin","year":"2016","unstructured":"Lin JCW, Fournier-Viger P, Gan W (2016) FHN: an efficient algorithm for mining high-utility itemsets with negative unit profits. Knowl Based Syst 111:283\u2013298","journal-title":"Knowl Based Syst"},{"key":"672_CR13","unstructured":"Liu C, Dong X, Li C, Li Y (2015) SAPNSP: select actionable positive and negative sequential patterns based on a contribution metric. In: Proceedings of the 12th international conference on fuzzy systems and knowledge discovery, pp 811\u2013815"},{"issue":"9","key":"672_CR14","first-page":"21","volume":"64","author":"B Mallick","year":"2013","unstructured":"Mallick B, Garg D, Grover PS (2013) CRM customer value based on constrained sequential pattern mining. Int J Comput Appl 64(9):21\u201329","journal-title":"Int J Comput Appl"},{"issue":"2","key":"672_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2431211.2431218","volume":"45","author":"CH Mooney","year":"2013","unstructured":"Mooney CH, Roddick JF (2013) Sequential pattern mining\u2014approaches and algorithms. ACM Comput Surv 45(2):1\u201339","journal-title":"ACM Comput Surv"},{"key":"672_CR16","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.revmed.2014.11.009","volume":"36","author":"G Moulis","year":"2015","unstructured":"Moulis G, Lapeyre-Mestre M, Palmaro A, Pugnet G, Montastruc JL, Sailler L (2015) French health insurance databases: what interest for medical research? La Revue de M\u00e9decine Interne 36:411\u2013417","journal-title":"La Revue de M\u00e9decine Interne"},{"key":"672_CR17","doi-asserted-by":"crossref","unstructured":"Negrevergne B, Guns T (2015) Constraint-based sequence mining using constraint programming. In: Michel L (ed) Proceedings of the conference on integration of AI and OR techniques in constraint programming (CPAIOR). Springer International Publishing, Cham, pp 288\u2013305","DOI":"10.1007\/978-3-319-18008-3_20"},{"issue":"2, Part 2","key":"672_CR18","doi-asserted-by":"publisher","first-page":"2592","DOI":"10.1016\/j.eswa.2008.02.021","volume":"36","author":"E Ngai","year":"2009","unstructured":"Ngai E, Xiu L, Chau D (2009) Application of data mining techniques in customer relationship management: a literature review and classification. Expert Syst Appl 36(2, Part 2):2592\u20132602","journal-title":"Expert Syst Appl"},{"issue":"11","key":"672_CR19","doi-asserted-by":"publisher","first-page":"1424","DOI":"10.1109\/TKDE.2004.77","volume":"16","author":"J Pei","year":"2004","unstructured":"Pei J, Han J, Mortazavi-Asl B, Wang J, Pinto H, Chen Q, Dayal U, Hsu MC (2004) Mining sequential patterns by pattern-growth: the PrefixSpan approach. IEEE Trans Knowl Data Eng 16(11):1424\u20131440","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"2","key":"672_CR20","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s10844-006-0006-z","volume":"28","author":"J Pei","year":"2007","unstructured":"Pei J, Han J, Wang W (2007) Constraint-based sequential pattern mining: the pattern-growth methods. J Intell Inf Syst 28(2):133\u2013160","journal-title":"J Intell Inf Syst"},{"key":"672_CR21","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1002\/pds.3879","volume":"24","author":"E Polard","year":"2015","unstructured":"Polard E, Nowak E, Happe A, Biraben A, Oger E (2015) Brand name to generic substitution of antiepileptic drugs does not lead to seizure-related hospitalization: a population-based case-crossover study. Pharmacoepidemiol Drug Saf 24:1161\u20131169","journal-title":"Pharmacoepidemiol Drug Saf"},{"key":"672_CR22","doi-asserted-by":"crossref","unstructured":"Qiu P, Zhao L, Dong X (2017) NegI-NSP: negative sequential pattern mining based on loose constraints. In: Proceedings of the 43rd annual conference of the IEEE industrial electronics society (IECON), pp 3419\u20133425","DOI":"10.1109\/IECON.2017.8216579"},{"key":"672_CR23","doi-asserted-by":"crossref","unstructured":"Srikant R, Agrawal R (1996) Mining sequential patterns: Generalizations and performance improvements. In: Proceedings of the international conference on extending database technology (EDBT). Springer, pp 1\u201317","DOI":"10.1007\/BFb0014140"},{"issue":"2","key":"672_CR24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3214306","volume":"52","author":"W Wang","year":"2019","unstructured":"Wang W, Cao L (2019) Negative sequences analysis: a review. ACM Comput Surv 52(2):1\u201339","journal-title":"ACM Comput Surv"},{"issue":"10","key":"672_CR25","doi-asserted-by":"publisher","first-page":"1750035","DOI":"10.1142\/S0218001417500355","volume":"31","author":"T Xu","year":"2017","unstructured":"Xu T, Dong X, Xu J, Dong X (2017a) Mining high utility sequential patterns with negative item values. Int J Pattern Recognit Artif Intell 31(10):1750035","journal-title":"Int J Pattern Recognit Artif Intell"},{"issue":"02","key":"672_CR26","doi-asserted-by":"publisher","first-page":"1750003","DOI":"10.1142\/S0218001417500033","volume":"31","author":"T Xu","year":"2017","unstructured":"Xu T, Dong X, Xu J, Gong Y (2017b) E-msNSP: efficient negative sequential patterns mining based on multiple minimum supports. Int J Pattern Recognit Artif Intell 31(02):1750003","journal-title":"Int J Pattern Recognit Artif Intell"},{"key":"672_CR27","doi-asserted-by":"publisher","first-page":"23839","DOI":"10.1109\/ACCESS.2018.2827167","volume":"6","author":"T Xu","year":"2018","unstructured":"Xu T, Li T, Dong X (2018) Efficient high utility negative sequential patterns mining in smart campus. IEEE Access 6:23839\u201323847","journal-title":"IEEE Access"},{"issue":"1\/2","key":"672_CR28","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1023\/A:1007652502315","volume":"42","author":"MJ Zaki","year":"2001","unstructured":"Zaki MJ (2001) SPADE: an efficient algorithm for mining frequent sequences. Mach Learn 42(1\/2):31\u201360","journal-title":"Mach Learn"},{"key":"672_CR29","unstructured":"Zheng Z, Zhao Y, Zuo Z, Cao L (2009) Negative-GSP: an efficient method for mining negative sequential patterns. In: Proceedings of the Australasian data mining conference, pp 63\u201367"},{"key":"672_CR30","doi-asserted-by":"crossref","unstructured":"Zheng Z, Zhao Y, Zuo Z, Cao L (2010) An efficient GA-based algorithm for mining negative sequential patterns. In: Proceedings of the Pacific-Asia conference on knowledge discovery and data mining (PAKDD). Springer, pp 262\u2013273","DOI":"10.1007\/978-3-642-13657-3_30"}],"container-title":["Data Mining and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-019-00672-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10618-019-00672-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-019-00672-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T05:04:35Z","timestamp":1665551075000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10618-019-00672-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,21]]},"references-count":30,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["672"],"URL":"https:\/\/doi.org\/10.1007\/s10618-019-00672-w","relation":{},"ISSN":["1384-5810","1573-756X"],"issn-type":[{"value":"1384-5810","type":"print"},{"value":"1573-756X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,21]]},"assertion":[{"value":"21 August 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}