{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T21:37:24Z","timestamp":1773524244402,"version":"3.50.1"},"reference-count":73,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"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":["Neural Process Lett"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s11063-022-10793-x","type":"journal-article","created":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T18:23:17Z","timestamp":1647973397000},"page":"3913-3939","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Discovery of Interesting Itemsets for Web Service Composition Using Hybrid Genetic Algorithm"],"prefix":"10.1007","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8606-7278","authenticated-orcid":false,"given":"S.","family":"Kannimuthu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D. Gowtham","family":"Chakravarthy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,22]]},"reference":[{"issue":"6","key":"10793_CR1","doi-asserted-by":"publisher","first-page":"866","DOI":"10.1109\/69.553155","volume":"8","author":"MS Chen","year":"1996","unstructured":"Chen MS, Han J, Yu PS (1996) Data mining: an overview from a database perspective. IEEE Trans Knowl Data Eng 8(6):866\u2013883. https:\/\/doi.org\/10.1109\/69.553155","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"10793_CR2","volume-title":"Data mining: concepts and techniques","author":"J Han","year":"2011","unstructured":"Han J, Pei J, Kamber M (2011) Data mining: concepts and techniques. Elsevier, New York"},{"issue":"3","key":"10793_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1132960.1132963","volume":"38","author":"L Geng","year":"2006","unstructured":"Geng L, Hamilton HJ (2006) Interestingness measures for data mining: a survey. ACM Comput Surv 38(3):1\u201332. https:\/\/doi.org\/10.1145\/1132960.1132963","journal-title":"ACM Comput Surv"},{"key":"10793_CR4","unstructured":"George B, Plexousakis D (2010) Automated web service composition: state of the art and research challenges. ICS-FORTH, Technical Report-409"},{"key":"10793_CR5","doi-asserted-by":"publisher","unstructured":"Rathore M, Suman U (2013) Web service selection algorithm for dynamic service composition using LSLO approach, In: Proceedings of 2013 international conference on informatics, electronics and vision (ICIEV), pp 1\u20136. doi: https:\/\/doi.org\/10.1109\/ICIEV.2013.6572688.","DOI":"10.1109\/ICIEV.2013.6572688"},{"issue":"2","key":"10793_CR6","doi-asserted-by":"publisher","first-page":"83","DOI":"10.5121\/ijdkp.2016.6207","volume":"6","author":"R Vivek","year":"2016","unstructured":"Vivek R, Prasad M, Sushmitha N (2016) Recommendation for web service Composition by mining usage logs. Int J Data Mining Knowle Manage Process 6(2):83\u201389. https:\/\/doi.org\/10.5121\/ijdkp.2016.6207","journal-title":"Int J Data Mining Knowle Manage Process"},{"issue":"2","key":"10793_CR7","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s11761-008-0023-6","volume":"2","author":"G Walid","year":"2008","unstructured":"Walid G, Ba\u00efna K, Godart C (2008) Log-based mining techniques applied to web service composition reengineering. Serv Oriented Comput Appl 2(2):93\u2013110. https:\/\/doi.org\/10.1007\/s11761-008-0023-6","journal-title":"Serv Oriented Comput Appl"},{"key":"10793_CR8","volume-title":"Genetic algorithms in search, optimization, and machine learning","author":"DE Goldberg","year":"1989","unstructured":"Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Bosten"},{"issue":"2","key":"10793_CR9","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TEVC.2007.895271","volume":"12","author":"C Perales-Gravan","year":"2008","unstructured":"Perales-Gravan C, Lahoz-Beltra R (2008) An AM Radio Receiver designed with a genetic algorithm based on a bacterial conjugation genetic operator. IEEE Trans Evol Comput 12(2):129\u2013142. https:\/\/doi.org\/10.1109\/TEVC.2007.895271","journal-title":"IEEE Trans Evol Comput"},{"key":"10793_CR10","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1038\/330033a0","volume":"330","author":"WH Calvin","year":"1987","unstructured":"Calvin WH (1987) The brain as a Darwin machine. Nature 330:33\u201334. https:\/\/doi.org\/10.1038\/330033a0","journal-title":"Nature"},{"key":"10793_CR11","doi-asserted-by":"publisher","unstructured":"Liu Y, Liao WK, Choudhary A (2005) A two-phase algorithm for fast discovery of high utility Itemsets. In: 9th Pacific-Asia conference on advances in knowledge discovery and data mining (PAKDD 2005), Lecturer Notes Computer Science, vol 3518, pp 689\u2013695. doi: https:\/\/doi.org\/10.1007\/11430919_79.","DOI":"10.1007\/11430919_79"},{"key":"10793_CR12","doi-asserted-by":"publisher","unstructured":"Chan R, Yang Q, Shen Y (2003) Mining high-utility itemsets. In: Proceedings of the 2003 IEEE international conference on data mining (ICDM\u2019 03) Melbourne, FL, pp 19\u201326. doi: https:\/\/doi.org\/10.1109\/ICDM.2003.1250893.","DOI":"10.1109\/ICDM.2003.1250893"},{"key":"10793_CR13","doi-asserted-by":"publisher","unstructured":"Yao H, Hamilton HJ, Butz CJ (2004) A foundational approach to mining itemset utilities from databases. In: Proceedings of the 3rd SIAM international conference on data mining, Orlando, Florida, pp 482\u2013486. doi: https:\/\/doi.org\/10.1137\/1.9781611972740.51.","DOI":"10.1137\/1.9781611972740.51"},{"key":"10793_CR14","doi-asserted-by":"publisher","unstructured":"Liu Y, Liao WK, Choudhary A (2005) A fast high utility itemsets mining algorithm. UBDM\u20192005, pp 90\u201399. doi: https:\/\/doi.org\/10.1145\/1089827.1089839.","DOI":"10.1145\/1089827.1089839"},{"issue":"4","key":"10793_CR15","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/4434.806975","volume":"7","author":"MJ Zaki","year":"1999","unstructured":"Zaki MJ (1999) Parallel and distributed association mining: a survey. IEEE Concurr 7(4):4\u201325. https:\/\/doi.org\/10.1109\/4434.806975","journal-title":"IEEE Concurr"},{"issue":"1","key":"10793_CR16","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. https:\/\/doi.org\/10.1023\/A:1007652502315","journal-title":"Mach Learn"},{"key":"10793_CR17","unstructured":"Yao H, Hamilton HJ, Geng L (2006) A unified framework for utility based measures for mining itemsets. In: Proceedings of the 2nd international workshop on utility-based data mining, pp 28\u201337"},{"issue":"3","key":"10793_CR18","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1016\/j.datak.2005.10.004","volume":"59","author":"H Yao","year":"2006","unstructured":"Yao H, Hamilton HJ (2006) Mining itemset utilities from transaction databases. Data Knowl Eng 59(3):603\u2013626. https:\/\/doi.org\/10.1016\/j.datak.2005.10.004","journal-title":"Data Knowl Eng"},{"key":"10793_CR19","doi-asserted-by":"publisher","unstructured":"Tseng VS, Chu CJ, Liang T (2006) Efficient mining of temporal high utility itemsets from data streams. In: Proceedings of the 2nd international workshop on utility-based data mining, pp 18\u201327. doi: https:\/\/doi.org\/10.1007\/978-3-642-13265-0_8.","DOI":"10.1007\/978-3-642-13265-0_8"},{"key":"10793_CR20","volume-title":"Advances in knowledge discovery and data mining","author":"U Fayyad","year":"1996","unstructured":"Fayyad U, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (1996) Advances in knowledge discovery and data mining. AAAI\/MIT Press, New York"},{"key":"10793_CR21","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1007\/978-3-540-72588-6_115","volume":"4489","author":"J Wang","year":"2007","unstructured":"Wang J, Liu Y, Zhou L, Shi Y, Zhu X (2007) Pushing frequency constraint to utility mining model. Lect Notes Comput Sci 4489:685\u2013692. https:\/\/doi.org\/10.1007\/978-3-540-72588-6_115","journal-title":"Lect Notes Comput Sci"},{"key":"10793_CR22","unstructured":"Podpecan V, Lavrac N, Kononenko I (2007) A fast algorithm for mining utility-frequent itemsets. In: Proceedings of the 11th European conference on principles and practice of knowledge discovery in databases."},{"issue":"11","key":"10793_CR23","doi-asserted-by":"publisher","first-page":"3317","DOI":"10.1016\/j.patcog.2007.02.003","volume":"40","author":"J Hu","year":"2007","unstructured":"Hu J, Mojsilovic A (2007) High-utility pattern mining: a method for discovery of high-utility item sets. Pattern Recogn 40(11):3317\u20133324. https:\/\/doi.org\/10.1016\/j.patcog.2007.02.003","journal-title":"Pattern Recogn"},{"key":"10793_CR24","doi-asserted-by":"publisher","unstructured":"Erwin A, Gopalan RP, Achuthan NR (2007) CTU-Mine: an efficient high utility itemset mining algorithm using the pattern growth approach. In: Proceedings of 7th international conference on computer and information technology, pp 71\u201376. Doi: https:\/\/doi.org\/10.1109\/CIT.2007.120.","DOI":"10.1109\/CIT.2007.120"},{"key":"10793_CR25","unstructured":"Erwin A, Gopalan RP, Achuthan NR (2007) A bottom-up projection based algorithm for mining high utility itemsets. In: 2nd workshop on integrating AI and data mining (AIDM 2007), pp 3\u201311"},{"key":"10793_CR26","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/978-3-540-74553-2_26","volume":"4654","author":"SJ Yen","year":"2007","unstructured":"Yen SJ, Lee YS (2007) Mining high utility quantitative association rules. Lect Notes Comput Sci 4654:283\u2013292. https:\/\/doi.org\/10.1007\/978-3-540-74553-2_26","journal-title":"Lect Notes Comput Sci"},{"issue":"1","key":"10793_CR27","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1016\/j.datak.2007.06.009","volume":"64","author":"YC Li","year":"2008","unstructured":"Li YC, Yeh JS, Chang CC (2008) Isolated items discarding strategy for discovering high utility itemsets. Data Knowl Eng 64(1):198\u2013217. https:\/\/doi.org\/10.1016\/j.datak.2007.06.009","journal-title":"Data Knowl Eng"},{"issue":"12","key":"10793_CR28","doi-asserted-by":"publisher","first-page":"1708","DOI":"10.1109\/TKDE.2009.46","volume":"21","author":"CF Ahmed","year":"2009","unstructured":"Ahmed CF, Tanbeer SK, Jeong BS, Lee YK (2009) Efficient tree structures for high utility pattern mining in incremental databases. IEEE Trans Knowl Data Eng 21(12):1708\u20131721. https:\/\/doi.org\/10.1109\/TKDE.2009.46","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"10793_CR29","unstructured":"Lan GC, Hong TP, Tseng VS (2009) Mining On-shelf high utility itemsets. In: International conference on information technology and applications in outlying islands, pp 482\u2013489"},{"issue":"2","key":"10793_CR30","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1016\/j.amc.2009.05.066","volume":"215","author":"CJ Chu","year":"2009","unstructured":"Chu CJ, Tseng VS, Liang T (2009) An efficient algorithm for mining high utility itemsets with negative item values in large databases. J Appl Math Comput 215(2):767\u2013778. https:\/\/doi.org\/10.1016\/j.amc.2009.05.066","journal-title":"J Appl Math Comput"},{"key":"10793_CR31","doi-asserted-by":"publisher","unstructured":"Ahmed CF, Tanbeer SK, Jeong BS (2009) Efficient mining of weighted frequent patterns over data streams. In: Eleventh IEEE international conference on high performance computing and communications, pp 400\u2013406. Doi: https:\/\/doi.org\/10.1109\/HPCC.2009.36.","DOI":"10.1109\/HPCC.2009.36"},{"key":"10793_CR32","doi-asserted-by":"publisher","unstructured":"Tseng VS, Wu CW, Shie BE, Yu PS (2010) UP-growth: an efficient algorithm for high utility itemset mining. In: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 253\u2013262. doi: https:\/\/doi.org\/10.1145\/1835804.1835839.","DOI":"10.1145\/1835804.1835839"},{"issue":"5","key":"10793_CR33","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1177\/0165551511416436","volume":"37","author":"HF Li","year":"2011","unstructured":"Li HF (2011) MHUI-max: An efficient algorithm for discovering high-utility itemsets from data streams. Inf Sci 37(5):532\u2013545. https:\/\/doi.org\/10.1177\/0165551511416436","journal-title":"Inf Sci"},{"issue":"7","key":"10793_CR34","doi-asserted-by":"publisher","first-page":"8259","DOI":"10.1016\/j.eswa.2011.01.006","volume":"38","author":"TP Hong","year":"2011","unstructured":"Hong TP, Lee CH, Wang SL (2011) Effective utility mining with the measure of average utility. Expert Syst Appl 38(7):8259\u20138265. https:\/\/doi.org\/10.1016\/j.eswa.2011.01.006","journal-title":"Expert Syst Appl"},{"key":"10793_CR35","doi-asserted-by":"publisher","unstructured":"Li FG, Sun YJ, Ni ZW, Yu L, Mao XM (2012) The Utility Frequent Pattern Mining Based on Slide Window in Data Stream. In: 5th international conference on intelligent computation technology and automation (ICICTA), pp 414\u2013419. doi: https:\/\/doi.org\/10.1109\/ICICTA.2012.110.","DOI":"10.1109\/ICICTA.2012.110"},{"issue":"6","key":"10793_CR36","first-page":"1597","volume":"31","author":"S Kannimuthu","year":"2012","unstructured":"Kannimuthu S, Premalatha S, Shankar S (2012) A novel approach to extract high utility itemsets from distributed databases. Comput Inform 31(6):1597\u20131615","journal-title":"Comput Inform"},{"issue":"8","key":"10793_CR37","doi-asserted-by":"publisher","first-page":"7173","DOI":"10.1016\/j.eswa.2012.01.072","volume":"39","author":"CW Lin","year":"2012","unstructured":"Lin CW, Lan GC, Hong TP (2012) An incremental mining algorithm for high utility itemsets. Expert Syst Appl 39(8):7173\u20137180. https:\/\/doi.org\/10.1016\/j.eswa.2012.01.072","journal-title":"Expert Syst Appl"},{"issue":"17","key":"10793_CR38","doi-asserted-by":"publisher","first-page":"12947","DOI":"10.1016\/j.eswa.2012.05.035","volume":"39","author":"BE Shie","year":"2012","unstructured":"Shie BE, Yu PS, Tseng VS (2012) Efficient algorithms for mining maximal high utility itemsets from data streams with different models. Expert Syst Appl 39(17):12947\u201312960. https:\/\/doi.org\/10.1016\/j.eswa.2012.05.035","journal-title":"Expert Syst Appl"},{"issue":"20","key":"10793_CR39","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.ins.2014.01.045","volume":"285","author":"M Zihayat","year":"2014","unstructured":"Zihayat M, An A (2014) Mining top-k high utility patterns over data streams. J Inf Sci 285(20):138\u2013161. https:\/\/doi.org\/10.1016\/j.ins.2014.01.045","journal-title":"J Inf Sci"},{"issue":"11","key":"10793_CR40","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 TP, Tseng VS, Wang SL (2014) Applying the maximum utility measure in high utility sequential pattern mining. Expert Syst Appl 41(11):5071\u20135081. https:\/\/doi.org\/10.1016\/j.eswa.2014.02.022","journal-title":"Expert Syst Appl"},{"key":"10793_CR41","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.knosys.2015.04.004","volume":"84","author":"X Zhang","year":"2015","unstructured":"Zhang X, Deng ZH (2015) Mining summarization of high utility itemsets. Knowl Based Syst 84:67\u201377. https:\/\/doi.org\/10.1016\/j.knosys.2015.04.004","journal-title":"Knowl Based Syst"},{"issue":"3","key":"10793_CR42","doi-asserted-by":"publisher","first-page":"648","DOI":"10.1016\/j.aei.2015.06.002","volume":"29","author":"JC-W Lin","year":"2015","unstructured":"Lin JC-W, Gan W, Hong TP, Tseng VS (2015) Efficient algorithms for mining up-to-date high-utility patterns. Adv Eng Inform 29(3):648\u2013661. https:\/\/doi.org\/10.1016\/j.aei.2015.06.002","journal-title":"Adv Eng Inform"},{"issue":"3","key":"10793_CR43","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1016\/j.eswa.2014.08.037","volume":"42","author":"U Yun","year":"2015","unstructured":"Yun U, Kim J (2015) A fast perturbation algorithm using tree structure for privacy preserving utility mining. Expert Syst Appl 42(3):1149\u20131165. https:\/\/doi.org\/10.1016\/j.eswa.2014.08.037","journal-title":"Expert Syst Appl"},{"key":"10793_CR44","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.pisc.2015.11.013","volume":"7","author":"JC-W Lin","year":"2016","unstructured":"Lin JC-W, Gan W, Fournier-Viger P, Yang L, Liu Q, Frnda J, Sevcik L, Voznak M (2016) High utility-itemset mining and privacy-preserving utility mining. J Sci Perspect 7:74\u201380. https:\/\/doi.org\/10.1016\/j.pisc.2015.11.013","journal-title":"J Sci Perspect"},{"key":"10793_CR45","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.knosys.2015.12.019","volume":"96","author":"JC-W Lin","year":"2016","unstructured":"Lin JC-W, Gan W, Fournier-Viger P, Hong TP, Tseng VS (2016) Efficient algorithms for mining high-utility itemsets in uncertain databases. Knowl Based Syst 96:171\u2013187. https:\/\/doi.org\/10.1016\/j.knosys.2015.12.019","journal-title":"Knowl Based Syst"},{"key":"10793_CR46","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.bdr.2016.07.001","volume":"6","author":"Y Chen","year":"2016","unstructured":"Chen Y, An A (2016) Approximate parallel high utility itemset mining. Big Data Res 6:26\u201342. https:\/\/doi.org\/10.1016\/j.bdr.2016.07.001","journal-title":"Big Data Res"},{"key":"10793_CR47","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.knosys.2017.03.016","volume":"124","author":"U Yun","year":"2017","unstructured":"Yun U, Ryang H, Lee G, Fujita H (2017) An efficient algorithm for mining high utility patterns from incremental databases with one database scan. Knowl Based Syst 124:188\u2013206. https:\/\/doi.org\/10.1016\/j.knosys.2017.03.016","journal-title":"Knowl Based Syst"},{"key":"10793_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2017.12.035","volume":"145","author":"S Krishnamoorthy","year":"2018","unstructured":"Krishnamoorthy S (2018) Efficiently mining high utility itemsets with negative unit profits. Knowl Based Syst 145:1\u201314. https:\/\/doi.org\/10.1016\/j.knosys.2017.12.035","journal-title":"Knowl Based Syst"},{"key":"10793_CR49","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, Vo B, Fujita H (2019) An efficient method for mining high utility closed itemsets. J Inf Sci 495:78\u201399. https:\/\/doi.org\/10.1016\/j.ins.2019.05.006","journal-title":"J Inf Sci"},{"key":"10793_CR50","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ins.2020.03.030","volume":"529","author":"H Nam","year":"2020","unstructured":"Nam H, Yun U, Yoon E, Lin JC (2020) Efficient approach of recent high utility stream pattern mining with indexed list structure and pruning strategy considering arrival times of transactions. J Inf Sci 529:1\u201327. https:\/\/doi.org\/10.1016\/j.ins.2020.03.030","journal-title":"J Inf Sci"},{"key":"10793_CR51","doi-asserted-by":"publisher","first-page":"3788","DOI":"10.1109\/ACCESS.2020.2982415","volume":"50","author":"JC-W Lin","year":"2020","unstructured":"Lin JC-W, Pirouz M, Djenouri Y, Cheng CF, Ahmed U (2020) Incrementally updating the high average-utility patterns with pre-large concept. Appl Intell 50:3788\u20133807. https:\/\/doi.org\/10.1109\/ACCESS.2020.2982415","journal-title":"Appl Intell"},{"issue":"2","key":"10793_CR52","first-page":"65","volume":"4","author":"PFVT Truong","year":"2020","unstructured":"Truong PFVT, Tran A, Duong H, Le B (2020) EHUSM: mining high utility sequences with a pessimistic utility model. Data Sci Pattern Recogn 4(2):65\u201383","journal-title":"Data Sci Pattern Recogn"},{"issue":"16","key":"10793_CR53","doi-asserted-by":"publisher","first-page":"12669","DOI":"10.1109\/JIOT.2020.3026826","volume":"8","author":"G Srivastava","year":"2021","unstructured":"Srivastava G, Lin JC-W, Zhang X, Li Y (2021) Large-scale high-utility sequential pattern analytics in internet of things. IEEE Internet Things J 8(16):12669\u201312678. https:\/\/doi.org\/10.1109\/JIOT.2020.3026826","journal-title":"IEEE Internet Things J"},{"key":"10793_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107422","volume":"108","author":"JC-W Lin","year":"2021","unstructured":"Lin JC-W, Djenouri Y, Srivastava G, Yun U, Fournier-Viger P (2021) A predictive GA-based model for closed high-utility itemset mining. Appl Soft Comput 108:107422. https:\/\/doi.org\/10.1016\/j.asoc.2021.107422","journal-title":"Appl Soft Comput"},{"key":"10793_CR55","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.inffus.2021.05.011","volume":"76","author":"JC-W Lin","year":"2021","unstructured":"Lin JC-W, Djenouri Y, Srivastava G (2021) Efficient closed high-utility pattern fusion model in large-scale databases. Inf Fusion 76:122\u2013132. https:\/\/doi.org\/10.1016\/j.inffus.2021.05.011","journal-title":"Inf Fusion"},{"key":"10793_CR56","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1080\/08839514.2014.891839","volume":"28","author":"S Kannimuthu","year":"2014","unstructured":"Kannimuthu S, Premalatha K (2014) Discovery of high utility itemsets using genetic algorithm with ranked mutation. Appl Artif Intell 28:337\u2013359. https:\/\/doi.org\/10.1080\/08839514.2014.891839","journal-title":"Appl Artif Intell"},{"key":"10793_CR57","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-93040-4_1","volume":"10939","author":"W Song","year":"2018","unstructured":"Song W, Huang C (2018) Discovering high utility itemsets based on the artificial bee colony algorithm. PAKDD 2018. Lect Notes Comput Sci 10939:3\u201314. https:\/\/doi.org\/10.1007\/978-3-319-93040-4_1","journal-title":"Lect Notes Comput Sci"},{"key":"10793_CR58","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1016\/j.engappai.2016.07.006","volume":"55","author":"JC-W Lin","year":"2016","unstructured":"Lin JC-W, Yang L, Fournier-Viger P, Wu JMT, Hong TP, Wang LSL, Zhan J (2016) Mining high-utility itemsets based on particle swarm optimization. Eng Appl Artif Intell 55:320\u2013330. https:\/\/doi.org\/10.1016\/j.engappai.2016.07.006","journal-title":"Eng Appl Artif Intell"},{"key":"10793_CR59","doi-asserted-by":"publisher","first-page":"5103","DOI":"10.1007\/s00500-016-2106-1","volume":"21","author":"JC-W Lin","year":"2017","unstructured":"Lin JC-W, Yang L, Fournier-Viger P, Hong TP, Voznak M (2017) A binary PSO approach to mine high-utility itemsets. Soft Comput 21:5103\u20135121. https:\/\/doi.org\/10.1007\/s00500-016-2106-1","journal-title":"Soft Comput"},{"key":"10793_CR60","doi-asserted-by":"publisher","first-page":"19568","DOI":"10.1109\/ACCESS.2018.2819162","volume":"6","author":"W Song","year":"2018","unstructured":"Song W, Huang C (2018) Mining high utility itemsets using bio-inspired algorithms: a diverse optimal value framework. IEEE Access 6:19568\u201319582. https:\/\/doi.org\/10.1109\/ACCESS.2018.2819162","journal-title":"IEEE Access"},{"key":"10793_CR61","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105164","author":"R Gunawan","year":"2020","unstructured":"Gunawan R, Winarkoa E, Pulungana R (2020) A BPSO-based method for high-utility itemset mining without minimum utility threshold. Knowl Based Syst. https:\/\/doi.org\/10.1016\/j.knosys.2019.105164","journal-title":"Knowl Based Syst"},{"issue":"2","key":"10793_CR62","first-page":"19","volume":"4","author":"W Song","year":"2020","unstructured":"Song W, Huang C (2020) Mining high average-utility itemsets based on particle swarm optimization. Data Sci Pattern Recogn 4(2):19\u201332","journal-title":"Data Sci Pattern Recogn"},{"key":"10793_CR63","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-540-30480-7_22","volume":"3306","author":"R Nayak","year":"2004","unstructured":"Nayak R, Tong C (2004) Applications of data mining in web services. WISE 2004. Lect Notes Comput Sci 3306:199\u2013205. https:\/\/doi.org\/10.1007\/978-3-540-30480-7_22","journal-title":"Lect Notes Comput Sci"},{"key":"10793_CR64","doi-asserted-by":"publisher","unstructured":"Ran T, Zou Y (2010) An approach for mining web service composition patterns from execution logs. In: Proceedings of 12th IEEE international symposium on web systems evolution (WSE), Timisoara, pp 53\u201362. doi: https:\/\/doi.org\/10.1109\/WSE.2010.5623568.","DOI":"10.1109\/WSE.2010.5623568"},{"key":"10793_CR65","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.6531","author":"RZ Yasmina","year":"2021","unstructured":"Yasmina RZ, Fethallah H, Fadoua L (2021) Web service selection and composition based on uncertain quality of service. Concurrency Comput Pract Exp. https:\/\/doi.org\/10.1002\/cpe.6531","journal-title":"Concurrency Comput Pract Exp"},{"issue":"3","key":"10793_CR66","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s10732-010-9136-0","volume":"17","author":"G Zhang","year":"2011","unstructured":"Zhang G (2011) Quantum-inspired evolutionary algorithms: a survey and empirical study. J Heuristics 17(3):303\u2013351. https:\/\/doi.org\/10.1007\/s10732-010-9136-0","journal-title":"J Heuristics"},{"key":"10793_CR67","unstructured":"Mohammed AM, Elhefnawy NA, El-Sherbiny MM, Hadhoud MM (2012) Quantum crossover based quantum genetic algorithm for solving non-linear programming. In: 8th international conference on informatics and systems (INFOS2012), Cairo, Egypt, pp 145\u2013153"},{"key":"10793_CR68","unstructured":"SPMF: An open-source data mining library (2020) http:\/\/www.philippe-fournier-viger.com\/spmf\/index.php?link=algorithms.php. Accessed 6 Aug 2020"},{"key":"10793_CR69","unstructured":"IBM Synthetic Data Generation (2020) http:\/\/www.almaden.ibm.com\/software\/"},{"key":"10793_CR70","unstructured":"projects\/hdb\/resources.shtml. Accessed 6 Aug 2020"},{"key":"10793_CR71","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1214\/AOMS\/1177731944","volume":"11","author":"M Friedman","year":"1940","unstructured":"Friedman M (1940) A comparison of alternative tests of significance for the problem of m ranking. Ann Math Stat 11:86\u201392. https:\/\/doi.org\/10.1214\/AOMS\/1177731944","journal-title":"Ann Math Stat"},{"key":"10793_CR72","unstructured":"Nemenyi B (1963) Distribution-free multiple comparison. Dissertation, Princeton University."},{"key":"10793_CR73","first-page":"1","volume":"7","author":"J Demsar","year":"2006","unstructured":"Demsar J (2006) Statistical comparison of classifiers over multiple datasets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-022-10793-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-022-10793-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-022-10793-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T07:16:42Z","timestamp":1665731802000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-022-10793-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,22]]},"references-count":73,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["10793"],"URL":"https:\/\/doi.org\/10.1007\/s11063-022-10793-x","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,22]]},"assertion":[{"value":"28 February 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 March 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}