{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T05:27:29Z","timestamp":1775021249438,"version":"3.50.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2022,4]]},"DOI":"10.1007\/s10489-021-02520-1","type":"journal-article","created":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T05:04:32Z","timestamp":1630472672000},"page":"6106-6128","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Frequent high minimum average utility sequence mining with constraints in dynamic databases using efficient pruning strategies"],"prefix":"10.1007","volume":"52","author":[{"given":"Tin","family":"Truong","sequence":"first","affiliation":[]},{"given":"Hai","family":"Duong","sequence":"additional","affiliation":[]},{"given":"Bac","family":"Le","sequence":"additional","affiliation":[]},{"given":"Philippe","family":"Fournier-Viger","sequence":"additional","affiliation":[]},{"given":"Unil","family":"Yun","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,9,1]]},"reference":[{"issue":"5","key":"2520_CR1","doi-asserted-by":"publisher","first-page":"676","DOI":"10.4218\/etrij.10.1510.0066","volume":"32","author":"CF Ahmed","year":"2010","unstructured":"Ahmed CF, Tanbeer SK, Jeong BS (2010) A novel approach for mining high-utility sequential patterns in sequence databases. ETRI 32(5):676\u2013686","journal-title":"ETRI"},{"key":"2520_CR2","doi-asserted-by":"crossref","unstructured":"Ahmed CF, Tanbeer SK, Jeong BS (2010) Mining high utility web access sequences in dynamic web log data. In Proceedings of 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing, SNPD2010, pp.76\u201381","DOI":"10.1109\/SNPD.2010.21"},{"key":"2520_CR3","doi-asserted-by":"crossref","unstructured":"Shie BE, Cheng JH, Chuang KT, Tseng VS (2012) A one-phase method for mining high utility mobile sequential patterns in mobile commerce environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp.616\u2013626","DOI":"10.1007\/978-3-642-31087-4_63"},{"key":"2520_CR4","doi-asserted-by":"crossref","unstructured":"Shie BE, Hsiao HF, Tseng VS, Yu PS (2011) Mining high utility mobile sequential patterns in mobile commerce environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp.224\u2013238","DOI":"10.1007\/978-3-642-20149-3_18"},{"issue":"3","key":"2520_CR5","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1007\/s10489-012-0379-3","volume":"38","author":"BE Shie","year":"2013","unstructured":"Shie BE, Yu PS, Tseng VS (2013) Mining interesting user behavior patterns in mobile commerce environments. Appl Intell 38(3):418\u2013435","journal-title":"Appl Intell"},{"key":"2520_CR6","doi-asserted-by":"crossref","unstructured":"Gan W, Lin JC, Zhang J, Chao H, Fujita H, Yu PS (2020) ProUM: projection-based utility mining on sequence data. Inf. Sci. (Ny). 513 222\u2013240 Elsevier Inc.","DOI":"10.1016\/j.ins.2019.10.033"},{"key":"2520_CR7","doi-asserted-by":"crossref","unstructured":"Zihayat M, Davoudi H, An A (2017) Top-k utility-based gene regulation sequential pattern discovery. In Proceedings of 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016, pp.266\u2013273","DOI":"10.1109\/BIBM.2016.7822529"},{"issue":"1","key":"2520_CR8","first-page":"65","volume":"4","author":"T Truong","year":"2020","unstructured":"Truong T, Tran A, Duong H, Le B, Fournier-Viger P (2020) EHUSM : mining high utility sequences with a pessimistic utility model. Data Sci Pattern Recognit 4(1):65\u201383","journal-title":"Data Sci Pattern Recognit"},{"issue":"1","key":"2520_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.engappai.2019.05.010","volume":"85","author":"T Truong","year":"2019","unstructured":"Truong T, Duong H, Le B, Fournier-Viger P (2019) FMaxCloHUSM: An efficient algorithm for mining frequent closed and maximal high utility sequences. Eng Appl Artif Intell 85(1):1\u201320","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"2520_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15625\/1813-9663\/35\/1\/13234","volume":"35","author":"T Truong","year":"2019","unstructured":"Truong T, Tran A, Duong H, Le B (2019) Hupsmt: An efficient algorithm for mining high utility-probability sequences in uncertain databases with multiple minimum utility thresholds. Comput Sci Cybern 35(1):1\u201320","journal-title":"Comput Sci Cybern"},{"issue":"11","key":"2520_CR11","doi-asserted-by":"publisher","first-page":"5071","DOI":"10.1016\/j.eswa.2014.02.022","volume":"41","author":"GC Lan","year":"2014","unstructured":"Lan GC, Hong T-P, Tseng VS, Wang SL (2014) Applying the maximum utility measure in high utility sequential pattern mining. Expert Syst Appl 41(11):5071\u20135081","journal-title":"Expert Syst Appl"},{"key":"2520_CR12","doi-asserted-by":"crossref","unstructured":"Yin J, Zheng Z, Cao L (2012) USpan: An efficient algorithm for mining high utility sequential patterns. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.660\u2013668","DOI":"10.1145\/2339530.2339636"},{"issue":"1","key":"2520_CR13","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):31\u201360","journal-title":"Mach Learn"},{"key":"2520_CR14","unstructured":"Pei J, Han J, Mortazavi-Asl B, Pinto H, Chen Q, Dayal U, et al. (2001) PrefixSpan: mining sequential patterns by prefix-projected growth. In Proceedings of the 17th International Conference on Data Engineering, pp.215\u2013224"},{"key":"2520_CR15","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Gomariz A, Campos M (2014) Fast vertical Mining of Sequential Patterns Using co-occurrence Information. In Proceedings of 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD \u20182014, pp.40\u201352","DOI":"10.1007\/978-3-319-06608-0_4"},{"issue":"2","key":"2520_CR16","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/s10115-015-0914-8","volume":"49","author":"JZ Wang","year":"2016","unstructured":"Wang JZ, Huang JL, Chen YC (2016) On efficiently mining high utility sequential patterns. Knowl Inf Syst 49(2):597\u2013627","journal-title":"Knowl Inf Syst"},{"key":"2520_CR17","doi-asserted-by":"crossref","unstructured":"Truong T, Fournier-Viger P (2019) A survey of high utility sequential pattern mining. In P. Fournier-Viger, J. C.-W. Lin, R. Nkambou, V. Bay, & V. S. Tseng, High-Utility Pattern Mining: Theory, Algorithms and Applications, pp.97\u2013129","DOI":"10.1007\/978-3-030-04921-8_4"},{"issue":"2","key":"2520_CR18","first-page":"1","volume":"1904","author":"W Gan","year":"2019","unstructured":"Gan W, Lin JC-W, Zhang J, Fournier-Viger P, Chao H, Yu PS (2019) Fast utility mining on complex sequences. CoRR 1904(2):1\u201315","journal-title":"CoRR"},{"issue":"7","key":"2520_CR19","doi-asserted-by":"publisher","first-page":"8259","DOI":"10.1016\/j.eswa.2011.01.006","volume":"38","author":"T-P Hong","year":"2011","unstructured":"Hong T-P, Lee CH, Wang SL (2011) Effective utility mining with the measure of average utility. Expert Syst Appl 38(7):8259\u20138265","journal-title":"Expert Syst Appl"},{"issue":"05","key":"2520_CR20","doi-asserted-by":"publisher","first-page":"1009","DOI":"10.1142\/S0219622012500307","volume":"11","author":"GC Lan","year":"2012","unstructured":"Lan GC, Hong T-P, Tseng VS (2012) Efficiently mining high average-utility Itemsets with an improved upper-bound strategy. Inf Technol Decis Mak 11(05):1009\u20131030","journal-title":"Inf Technol Decis Mak"},{"issue":"8","key":"2520_CR21","doi-asserted-by":"publisher","first-page":"7593","DOI":"10.1109\/ACCESS.2018.2801261","volume":"6","author":"JC-W Lin","year":"2018","unstructured":"Lin JC-W, Ren S, Fournier-Viger P (2018) MEMU: more efficient algorithm to mine high average-utility patterns with multiple minimum average-utility thresholds. IEEE Access 6(8):7593\u20137609","journal-title":"IEEE Access"},{"issue":"8","key":"2520_CR22","doi-asserted-by":"publisher","first-page":"12927","DOI":"10.1109\/ACCESS.2017.2717438","volume":"5","author":"JC-W Lin","year":"2017","unstructured":"Lin JC-W, Ren S, Fournier-Viger P, Hong T-P (2017) EHAUPM: efficient high average-utility pattern mining with tighter upper bounds. IEEE Access 5(8):12927\u201312940","journal-title":"IEEE Access"},{"issue":"1","key":"2520_CR23","doi-asserted-by":"publisher","first-page":"18655","DOI":"10.1109\/ACCESS.2018.2820740","volume":"6","author":"JMT Wu","year":"2018","unstructured":"Wu JMT, Lin JC-W, Pirouz M, Fournier-Viger P (2018) TUB-HAUPM: tighter upper bound for mining high average-utility patterns. IEEE Access 6(1):18655\u201318669","journal-title":"IEEE Access"},{"issue":"1","key":"2520_CR24","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.future.2016.10.027","volume":"68","author":"U Yun","year":"2017","unstructured":"Yun U, Kim D (2017) Mining of high average-utility itemsets using novel list structure and pruning strategy. Futur Gener Comput Syst 68(1):346\u2013360","journal-title":"Futur Gener Comput Syst"},{"issue":"1","key":"2520_CR25","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1016\/j.protcy.2012.10.053","volume":"6","author":"M Thilagu","year":"2012","unstructured":"Thilagu M, Nadarajan R (2012) Efficiently Mining of Effective web Traversal Patterns with average utility. Procedia Technol 6(1):444\u2013451","journal-title":"Procedia Technol"},{"issue":"1","key":"2520_CR26","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.ins.2019.11.018","volume":"515","author":"T Truong","year":"2020","unstructured":"Truong T, Duong H, Le B, Fournier-Viger P (2020) EHAUSM: An efficient algorithm for high average utility sequence mining. Inf Sci (Ny) 515(1):302\u2013323","journal-title":"Inf Sci (Ny)"},{"key":"2520_CR27","doi-asserted-by":"publisher","first-page":"105241","DOI":"10.1016\/j.knosys.2019.105241","volume":"191","author":"P Fournier-Viger","year":"2020","unstructured":"Fournier-Viger P, Li J, Lin JC-W, Truong T, Uday Kiran R (2020) Mining cost-effective patterns in event logs. Knowledge-Based Syst 191:105241","journal-title":"Knowledge-Based Syst"},{"issue":"1","key":"2520_CR28","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.knosys.2019.03.022","volume":"175","author":"LTT Nguyen","year":"2019","unstructured":"Nguyen LTT, Nguyen P, Nguyen TDD, Vo B, Fournier-Viger P, Tseng VS (2019) Mining high-utility itemsets in dynamic profit databases. Knowledge-Based Syst 175(1):130\u2013144","journal-title":"Knowledge-Based Syst"},{"issue":"10","key":"2520_CR29","doi-asserted-by":"publisher","first-page":"2645","DOI":"10.1109\/TKDE.2015.2420557","volume":"27","author":"OK Alkan","year":"2015","unstructured":"Alkan OK, Karagoz P (2015) CRoM and HuspExt: improving efficiency of high utility sequential pattern extraction. IEEE Trans Knowl Data Eng 27(10):2645\u20132657","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2520_CR30","doi-asserted-by":"crossref","unstructured":"Reddy PPC, Uday Kiran R, Zettsu K, Toyoda M, Krishna Reddy P, Kitsuregawa M (2019) Discovering spatial high utility frequent Itemsets in spatiotemporal databases. In Proceedings of International Conference on Big Data Analytics (BDA 2019), pp.287\u2013306","DOI":"10.1007\/978-3-030-37188-3_17"},{"key":"2520_CR31","doi-asserted-by":"crossref","unstructured":"Liu Y, Liao W, Choudhary A (2005) A fast high utility itemsets mining algorithm. In Proceedings of the 1st international workshop on Utility-based data mining, pp.90\u201399","DOI":"10.1145\/1089827.1089839"},{"issue":"2","key":"2520_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/01969722.2019.1705549","volume":"51","author":"LTT Nguyen","year":"2020","unstructured":"Nguyen LTT, Vu D, Nguyen TDD, Vo B (2020) Mining maximal high utility Itemsets on dynamic profit databases. Cybern Syst 51(2):1\u201321 Taylor & Francis","journal-title":"Cybern Syst"},{"key":"2520_CR33","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.ins.2019.05.006","volume":"495","author":"LTT Nguyen","year":"2019","unstructured":"Nguyen LTT, Vu VV, Lam MTH, Duong TTM, Manh LT, Nguyen TTT et al (2019) An efficient method for mining high utility closed itemsets. Inf Sci (NY) 495:78\u201399 Elsevier Inc","journal-title":"Inf Sci (NY)"},{"key":"2520_CR34","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1016\/j.ins.2019.07.005","volume":"504","author":"W Gan","year":"2019","unstructured":"Gan W, Lin JC, Chao H, Fujita H, Yu PS (2019) Correlated utility-based pattern mining. Inf Sci (NY) 504:470\u2013486 Elsevier Inc","journal-title":"Inf Sci (NY)"},{"issue":"2","key":"2520_CR35","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1109\/TKDE.2018.2833478","volume":"31","author":"T Truong","year":"2018","unstructured":"Truong T, Duong H, Le B, Fournier-Viger P (2018) Efficient vertical Mining of High Average-Utility Itemsets Based on novel upper-bounds. IEEE Trans Knowl Data Eng 31(2):301\u2013314","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2520_CR36","doi-asserted-by":"crossref","unstructured":"Hong T-P, Lee CH, Wang SL (2009) Mining high average-utility itemsets. In Proceedings of IEEE International Conference on Systems, Man and Cybernetics, pp.2526\u20132530","DOI":"10.1109\/ICSMC.2009.5346333"},{"issue":"2","key":"2520_CR37","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/j.aei.2016.04.002","volume":"30","author":"JC-W Lin","year":"2016","unstructured":"Lin JC-W, Li T, Fournier-Viger P, Hong T-P, Zhan J, Voznak M (2016) An efficient algorithm to mine high average-utility itemsets. Adv Eng Informatics 30(2):233\u2013243","journal-title":"Adv Eng Informatics"},{"issue":"2","key":"2520_CR38","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1007\/s10489-017-0896-1","volume":"47","author":"JC-W Lin","year":"2017","unstructured":"Lin JC-W, Ren S, Fournier-Viger P, Hong T-P, Su J-H, Vo B (2017) A fast algorithm for mining high average-utility itemsets. Appl Intell 47(2):331\u2013346","journal-title":"Appl Intell"},{"key":"2520_CR39","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.ins.2020.07.043","volume":"543","author":"H Kim","year":"2021","unstructured":"Kim H, Yun U, Baek Y, Kim J, Vo B, Yoon E et al (2021) Efficient list based mining of high average utility patterns with maximum average pruning strategies. Inf Sci (NY) 543:85\u2013105 Elsevier Inc","journal-title":"Inf Sci (NY)"},{"issue":"1","key":"2520_CR40","doi-asserted-by":"publisher","first-page":"104847","DOI":"10.1016\/j.knosys.2019.07.018","volume":"183","author":"T Truong","year":"2019","unstructured":"Truong T, Duong H, Le B, Fournier-Viger P, Yun U (2019) Efficient high average-utility itemset mining using novel vertical weak upper-bounds. Knowledge-Based Syst 183(1):104847","journal-title":"Knowledge-Based Syst"},{"issue":"12","key":"2520_CR41","doi-asserted-by":"publisher","first-page":"4348","DOI":"10.1007\/s10489-019-01492-7","volume":"49","author":"R Wu","year":"2019","unstructured":"Wu R, Li Q, Chen X (2019) Mining contrast sequential pattern based on subsequence time distribution variation with discreteness constraints. Appl Intell 49(12):4348\u20134360","journal-title":"Appl Intell"},{"issue":"2","key":"2520_CR42","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. Intell Inf Syst 28(2):133\u2013160","journal-title":"Intell Inf Syst"},{"key":"2520_CR43","doi-asserted-by":"crossref","unstructured":"Zaki MJ (2000) Sequence mining in categorical domains: incorporating constraints. In Proceedings of the ninth international conference on Information and knowledge management, pp.422\u2013429","DOI":"10.1145\/354756.354849"},{"issue":"3","key":"2520_CR44","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/S0957-4174(03)00075-7","volume":"25","author":"YL Chen","year":"2003","unstructured":"Chen YL, Chiang MC, Ko MT (2003) Discovering time-interval sequential patterns in sequence databases. Expert Syst Appl 25(3):343\u2013354","journal-title":"Expert Syst Appl"},{"issue":"1","key":"2520_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2015.06.014","volume":"89","author":"J Zhang","year":"2015","unstructured":"Zhang J, Wang Y, Yang D (2015) CCSpan: mining closed contiguous sequential patterns. Knowledge-Based Syst 89(1):1\u201313","journal-title":"Knowledge-Based Syst"},{"issue":"1","key":"2520_CR46","first-page":"33","volume":"11","author":"B Mallick","year":"2014","unstructured":"Mallick B, Garg D, Grover PS (2014) Constraint-based sequential pattern mining: a pattern growth algorithm incorporating compactness, length and monetary. Inf Technol 11(1):33\u201342","journal-title":"Inf Technol"},{"issue":"04","key":"2520_CR47","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1142\/S0219622010003968","volume":"09","author":"U Yun","year":"2010","unstructured":"Yun U, Ryu KH (2010) Discovering important sequential patterns with length-decreasing weighted support constraints. Inf Technol Decis Mak 09(04):575\u2013599","journal-title":"Inf Technol Decis Mak"},{"issue":"2","key":"2520_CR48","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1007\/s10115-018-1161-6","volume":"57","author":"T Van","year":"2018","unstructured":"Van T, Vo B, Le B (2018) Mining sequential patterns with itemset constraints. Knowl Inf Syst 57(2):311\u2013330","journal-title":"Knowl Inf Syst"},{"issue":"11","key":"2520_CR49","doi-asserted-by":"publisher","first-page":"3902","DOI":"10.1007\/s10489-018-1182-6","volume":"48","author":"T Van","year":"2018","unstructured":"Van T, Yoshitaka A, Le B (2018) Mining web access patterns with super-pattern constraint. Appl Intell 48(11):3902\u20133914","journal-title":"Appl Intell"},{"issue":"1","key":"2520_CR50","first-page":"3389","volume":"15","author":"P Fournier-Viger","year":"2014","unstructured":"Fournier-Viger P, Lin JC-W, Gomaris A, Gueniche T, Soltani A, Deng Z et al (2014) SPMF: a Java open-source pattern mining library version 2. Mach Learn Res 15(1):3389\u20133393","journal-title":"Mach Learn Res"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-02520-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-021-02520-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-02520-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,13]],"date-time":"2022-04-13T04:15:45Z","timestamp":1649823345000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-021-02520-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,1]]},"references-count":50,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["2520"],"URL":"https:\/\/doi.org\/10.1007\/s10489-021-02520-1","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,1]]},"assertion":[{"value":"7 May 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 September 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}