{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T02:31:01Z","timestamp":1775010661324,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T00:00:00Z","timestamp":1657670400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T00:00:00Z","timestamp":1657670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100010229","name":"Natural Science Foundation of Tianjin Municipal Science and Technology Commission","doi-asserted-by":"publisher","award":["62073155"],"award-info":[{"award-number":["62073155"]}],"id":[{"id":"10.13039\/501100010229","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010229","name":"Natural Science Foundation of Tianjin Municipal Science and Technology Commission","doi-asserted-by":"publisher","award":["61673194"],"award-info":[{"award-number":["61673194"]}],"id":[{"id":"10.13039\/501100010229","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010229","name":"Natural Science Foundation of Tianjin Municipal Science and Technology Commission","doi-asserted-by":"publisher","award":["61672263"],"award-info":[{"award-number":["61672263"]}],"id":[{"id":"10.13039\/501100010229","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s10489-022-03850-4","type":"journal-article","created":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T07:03:46Z","timestamp":1657695826000},"page":"6992-7006","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["An efficient utility-list based high-utility itemset mining algorithm"],"prefix":"10.1007","volume":"53","author":[{"given":"Zaihe","family":"Cheng","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0750-4749","authenticated-orcid":false,"given":"Wei","family":"Fang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Jerry Chun-Wei","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Yuan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,7,13]]},"reference":[{"issue":"6","key":"3850_CR1","doi-asserted-by":"publisher","first-page":"1329","DOI":"10.1002\/wdm.1329","volume":"9","author":"JM Luna","year":"2019","unstructured":"Luna JM, Fournier-Viger P, Ventura S (2019) Frequent itemset mining: a 25 years review. WIREs Data Mining and Knowledge Discovery 9(6):1329. https:\/\/doi.org\/10.1002\/wdm.1329. https:\/\/wires.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/widm.1329","journal-title":"WIREs Data Mining and Knowledge Discovery"},{"key":"3850_CR2","doi-asserted-by":"publisher","first-page":"100146","DOI":"10.1016\/j.bdr.2020.100146","volume":"21","author":"P Goyal","year":"2020","unstructured":"Goyal P, Challa JS, Shrivastava S, Goyal N (2020) Anytime frequent itemset mining of transactional data streams. Big Data Research 21:100146. https:\/\/doi.org\/10.1016\/j.bdr.2020.100146","journal-title":"Big Data Research"},{"key":"3850_CR3","doi-asserted-by":"publisher","first-page":"113805","DOI":"10.1016\/j.eswa.2020.113805","volume":"163","author":"Y Xun","year":"2021","unstructured":"Xun Y, Cui X, Zhang J, Yin Q (2021) Incremental frequent itemsets mining based on frequent pattern tree and multi-scale. Expert Sys Appl 163:113805. https:\/\/doi.org\/10.1016\/j.eswa.2020.113805","journal-title":"Expert Sys Appl"},{"key":"3850_CR4","unstructured":"Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: International conference on very large data bases"},{"key":"3850_CR5","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Chun-Wei Lin J, Truong-Chi T, Nkambou R (2019) A Survey of High Utility Itemset Mining. In: Fournier-viger P, Lin JC-W, Nkambou R, Vo B, Tseng V.S. (eds) Springer, Cham, pp 1\u201345","DOI":"10.1007\/978-3-030-04921-8_1"},{"key":"3850_CR6","unstructured":"Karagoz P, Cekinel RF (2019) High-utility pattern mining: theory, algorithms and applications. In: Studies in big data, 2019"},{"key":"3850_CR7","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1016\/j.ins.2020.08.028","volume":"557","author":"X Han","year":"2020","unstructured":"Han X, Liu X, Li J, Gao H (2020) Efficient top-k high utility itemset mining on massive data. Inf Sci 557:382\u2013406. https:\/\/doi.org\/10.1016\/j.ins.08.028","journal-title":"Inf Sci"},{"issue":"4","key":"3850_CR8","doi-asserted-by":"publisher","first-page":"1306","DOI":"10.1109\/TKDE.2019.2942594","volume":"33","author":"W Gan","year":"2021","unstructured":"Gan W, Lin J C-W, Fournier-Viger P, Chao H.-C, Tseng VS, Yu PS (2021) A survey of utility-oriented pattern mining. IEEE Trans Knowl Data Eng 33(4):1306\u20131327. https:\/\/doi.org\/10.1109\/TKDE.2019.2942594","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3850_CR9","doi-asserted-by":"publisher","unstructured":"Amaranatha Reddy P, Hazarath Murali Krishna Prasad M (2021) High utility item-set mining from retail market data stream with various discount strategies using egui-tree. J Ambient Intell Human Comput, https:\/\/doi.org\/10.1007\/s12652-021-03341-3","DOI":"10.1007\/s12652-021-03341-3"},{"key":"3850_CR10","doi-asserted-by":"publisher","first-page":"115122","DOI":"10.1016\/j.eswa.2021.115122","volume":"181","author":"GJ Krishna","year":"2021","unstructured":"Krishna GJ, Ravi V (2021) High utility itemset mining using binary differential evolution: An application to customer segmentation. Expert Sys Appl 181:115122. https:\/\/doi.org\/10.1016\/j.eswa.2021.115122","journal-title":"Expert Sys Appl"},{"key":"3850_CR11","doi-asserted-by":"publisher","unstructured":"Kannimuthu S, Chakravarthy DG (2022) Discovery of interesting itemsets for web service composition using hybrid genetic algorithm. Neural Process Let, https:\/\/doi.org\/10.1007\/s11063-022-10793-x","DOI":"10.1007\/s11063-022-10793-x"},{"issue":"8","key":"3850_CR12","doi-asserted-by":"publisher","first-page":"1772","DOI":"10.1109\/TKDE.2012.59","volume":"25","author":"VS Tseng","year":"2013","unstructured":"Tseng VS, Shie BE, Wu CW, Yu PS (2013) Efficient algorithms for mining high utility itemsets from transactional databases. IEEE Trans Knowl Data Eng 25(8):1772\u20131786","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3850_CR13","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1016\/j.ins.2021.04.035","volume":"570","author":"C Zhang","year":"2021","unstructured":"Zhang C, Du Z, Gan W, Yu PS (2021) Tkus: Mining top-k high utility sequential patterns. Inf Sci 570:342\u2013359. https:\/\/doi.org\/10.1016\/j.ins.2021.04.035","journal-title":"Inf Sci"},{"key":"3850_CR14","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, Fujita H (2021) Efficient list based mining of high average utility patterns with maximum average pruning strategies. Inf Sci 543:85\u2013105. https:\/\/doi.org\/10.1016\/j.ins.2020.07.043","journal-title":"Inf Sci"},{"key":"3850_CR15","doi-asserted-by":"publisher","first-page":"107422","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":"3850_CR16","doi-asserted-by":"publisher","unstructured":"Singh K, Singh SS, Kumar A, Shakya HK, Biswas B (2018) Chn: an efficient algorithm for mining closed high utility itemsets with negative utility. IEEE Trans Knowl Data Eng:1\u20131 (ealy access). https:\/\/doi.org\/10.1109\/TKDE.2018.2882421","DOI":"10.1109\/TKDE.2018.2882421"},{"key":"3850_CR17","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, Chun- Wei Lin J (2020) Efficient approach of recent high utility stream pattern mining with indexed list structure and pruning strategy considering arrival times of transactions. Inf Sci 529:1\u201327. https:\/\/doi.org\/10.1016\/j.ins.2020.03.030","journal-title":"Inf Sci"},{"issue":"3","key":"3850_CR18","doi-asserted-by":"publisher","first-page":"1078","DOI":"10.1007\/s10489-018-1316-x","volume":"49","author":"K Singh","year":"2019","unstructured":"Singh K, Singh SS, Kumar A, Biswas B (2019) Tkeh: an efficient algorithm for mining top-k high utility itemsets. Appl Intell 49(3):1078\u20131097. https:\/\/doi.org\/10.1007\/s10489-018-1316-x","journal-title":"Appl Intell"},{"key":"3850_CR19","doi-asserted-by":"publisher","unstructured":"Song W, Zheng C, Huang C, Liu L (2021) Heuristically mining the top-k high-utility itemsets with cross-entropy optimization. Appl Intell, https:\/\/doi.org\/10.1007\/s10489-021-02576-z","DOI":"10.1007\/s10489-021-02576-z"},{"issue":"3","key":"3850_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-016-1020-2","volume":"52","author":"TL Dam","year":"2017","unstructured":"Dam TL, Li K, Fournier-Viger P, Duong QH (2017) An efficient algorithm for mining top- k on-shelf high utility itemsets. Knowl Inf Syst 52(3):1\u201335","journal-title":"Knowl Inf Syst"},{"issue":"4","key":"3850_CR21","doi-asserted-by":"publisher","first-page":"1240","DOI":"10.1007\/s10489-017-0939-7","volume":"47","author":"S Dawar","year":"2017","unstructured":"Dawar S, Sharma V, Goyal V (2017) Mining top-k high-utility itemsets from a data stream under sliding window model. Appl Intell 47(4):1240\u20131255. https:\/\/doi.org\/10.1007\/s10489-017-0939-7","journal-title":"Appl Intell"},{"key":"3850_CR22","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1016\/j.ins.2018.12.070","volume":"481","author":"P Fournier-Viger","year":"2019","unstructured":"Fournier-Viger P, Zhang Y, Chun-Wei Lin J, Fujita H, Koh YS (2019) Mining local and peak high utility itemsets. Inf Sci 481:344\u2013367","journal-title":"Inf Sci"},{"key":"3850_CR23","doi-asserted-by":"crossref","unstructured":"Truong T, Duong H, Le B, Fournier-Viger P (2020) Ehausm: an efficient algorithm for high average utility sequence mining. Inf Sci 515:302\u2013323","DOI":"10.1016\/j.ins.2019.11.018"},{"issue":"4","key":"3850_CR24","doi-asserted-by":"publisher","first-page":"3901","DOI":"10.1007\/s10489-021-02611-z","volume":"52","author":"K Singh","year":"2022","unstructured":"Singh K, Kumar R, Biswas B (2022) High average-utility itemsets mining: a survey. Appl Intell 52(4):3901\u20133938. https:\/\/doi.org\/10.1007\/s10489-021-02611-z","journal-title":"Appl Intell"},{"key":"3850_CR25","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.ins.2019.03.050","volume":"489","author":"P Fournier-Viger","year":"2019","unstructured":"Fournier-Viger P, Li Z, Lin JC-W, Kiran RU, Fujita H (2019) Efficient algorithms to identify periodic patterns in multiple sequences. Inf Sci 489:205\u2013226","journal-title":"Inf Sci"},{"key":"3850_CR26","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1016\/j.ins.2021.12.024","volume":"587","author":"M Ashraf","year":"2022","unstructured":"Ashraf M, Abdelkader T, Rady S, Gharib TF (2022) Tkn: an efficient approach for discovering top-k high utility itemsets with positive or negative profits. Inf Sci 587:654\u2013678. https:\/\/doi.org\/10.1016\/j.ins.2021.12.024","journal-title":"Inf Sci"},{"key":"3850_CR27","doi-asserted-by":"publisher","unstructured":"Liu M, Qu J (2012) Mining high utility itemsets without candidate generation. In: Proceedings of the 21st ACM international conference on information and knowledge management, CIKM \u201912, pp 55\u201364. Association for computing machinery, New York, https:\/\/doi.org\/10.1145\/2396761.2396773","DOI":"10.1145\/2396761.2396773"},{"issue":"5","key":"3850_CR28","doi-asserted-by":"publisher","first-page":"2371","DOI":"10.1016\/j.eswa.2014.11.001","volume":"42","author":"S Krishnamoorthy","year":"2015","unstructured":"Krishnamoorthy S (2015) Pruning strategies for mining high utility itemsets. Expert Syst Appl 42(5):2371\u20132381","journal-title":"Expert Syst Appl"},{"key":"3850_CR29","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Wu C-W, Zida S, Tseng VS (2014) Fhm: faster high-utility itemset mining using estimated utility co-occurrence pruning. In: International symposium on methodologies for intelligent systems, pp 83\u201392","DOI":"10.1007\/978-3-319-08326-1_9"},{"issue":"7","key":"3850_CR30","doi-asserted-by":"publisher","first-page":"1859","DOI":"10.1007\/s10489-017-1057-2","volume":"48","author":"Q-H Duong","year":"2018","unstructured":"Duong Q-H, Fournier-Viger P, Ramampiaro H, N\u00f8rv\u00e5g K, Dam T-L (2018) Efficient high utility itemset mining using buffered utility-lists. Appl Intell 48(7):1859\u20131877. https:\/\/doi.org\/10.1007\/s10489-017-1057-2","journal-title":"Appl Intell"},{"key":"3850_CR31","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.eswa.2017.08.028","volume":"90","author":"K Srikumar","year":"2017","unstructured":"Srikumar K (2017) Hminer: efficiently mining high utility itemsets. Expert Syst Appl 90:168\u2013183","journal-title":"Expert Syst Appl"},{"key":"3850_CR32","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.eswa.2018.03.041","volume":"105","author":"N Aryabarzan","year":"2018","unstructured":"Aryabarzan N, Minaei-Bidgoli B, Teshnehlab M (2018) negfin: an efficient algorithm for fast mining frequent itemsets. Expert Syst Appl 105:129\u2013143","journal-title":"Expert Syst Appl"},{"key":"3850_CR33","doi-asserted-by":"crossref","unstructured":"Liu Y, Liao W, Alok C (2005) A two-phase algorithm for fast discovery of high utility itemsets. In: Pacific-asia conference on advances in knowledge discovery & data mining","DOI":"10.1007\/11430919_79"},{"key":"3850_CR34","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1007\/978-3-319-27060-9_44","volume":"9413","author":"S Zida","year":"2015","unstructured":"Zida S, Fournier-Viger P, Lin JC-W, Wu C-W, Tseng VS (2015) Efim: a highly efficient algorithm for high-utility itemset mining. Adv Artif Intell Soft Comput 9413:530\u2013546","journal-title":"Adv Artif Intell Soft Comput"},{"key":"3850_CR35","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.knosys.2016.09.013","volume":"113","author":"JC-W Lin","year":"2016","unstructured":"Lin JC-W, Gan W, Fournier-Viger P, Hong T-P, Zhan J (2016) Efficient mining of high-utility itemsets using multiple minimum utility thresholds. Knowl-Based Syst 113:100\u2013115. https:\/\/doi.org\/10.1016\/j.knosys.2016.09.013","journal-title":"Knowl-Based Syst"},{"key":"3850_CR36","doi-asserted-by":"publisher","unstructured":"Peng A, Koh YS, Riddle P (2017) mhuiminer: a fast high utility itemset mining algorithm for sparse datasets:196\u2013207, https:\/\/doi.org\/10.1007\/978-3-319-57529-2_16","DOI":"10.1007\/978-3-319-57529-2_16"},{"key":"3850_CR37","doi-asserted-by":"publisher","unstructured":"Vuong N, Le B, Truong T, Nguyen D-P (2021) Efficient algorithms for discovering high-utility patterns with strong frequency affinities. Expert Syst Appl 169:114464. https:\/\/doi.org\/10.1016\/j.eswa.2020.114464","DOI":"10.1016\/j.eswa.2020.114464"},{"issue":"3","key":"3850_CR38","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1007\/s10489-017-0932-1","volume":"47","author":"S Dawar","year":"2017","unstructured":"Dawar S, Goyal V, Bera D (2017) A hybrid framework for mining high-utility itemsets in a sparse transaction database. Appl Intell 47(3):809\u2013827","journal-title":"Appl Intell"},{"issue":"1","key":"3850_CR39","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s10115-012-0492-y","volume":"38","author":"G Hong","year":"2014","unstructured":"Hong G, Hong T-P, Tseng VS (2014) An efficient projection-based indexing approach for mining high utility itemsets. Knowl Infn Syst 38(1):85\u2013107","journal-title":"Knowl Infn Syst"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03850-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03850-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03850-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T04:40:08Z","timestamp":1677472808000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03850-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,13]]},"references-count":39,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["3850"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03850-4","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,13]]},"assertion":[{"value":"3 June 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This work does not contain any studies with human participants performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Ethics approval and consent to participate"}},{"value":"Informed consent was obtained from all individual participants included in this work.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Consent for Publication"}},{"value":"The authors declare that they have no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}