{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T11:58:01Z","timestamp":1775044681693,"version":"3.50.1"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T00:00:00Z","timestamp":1612310400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T00:00:00Z","timestamp":1612310400000},"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\/s10489-020-02181-6","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T01:02:40Z","timestamp":1612314160000},"page":"6917-6938","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["TSPIN: mining top-k stable periodic patterns"],"prefix":"10.1007","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7680-9899","authenticated-orcid":false,"given":"Philippe","family":"Fournier-Viger","sequence":"first","affiliation":[]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Peng","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Jerry Chun-Wei","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Unil","family":"Yun","sequence":"additional","affiliation":[]},{"given":"Rage Uday","family":"Kiran","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,3]]},"reference":[{"key":"2181_CR1","doi-asserted-by":"crossref","unstructured":"Afriyie MK, Nofong VM, Wondoh J, Abdel-Fatao H (2020) Mining non-redundant periodic frequent patterns. In: Proceedings of the 12th Asian conference on intelligent information and database systems. Springer, pp 321\u2013331","DOI":"10.1007\/978-3-030-41964-6_28"},{"key":"2181_CR2","doi-asserted-by":"crossref","unstructured":"Agrawal R, Imielinski T, Swami AN (1993) Mining association rules between sets of items in large databases. In: Proceedings of the 19th ACM SIGMOD international conference on management of data. ACM, pp 207\u2013216","DOI":"10.1145\/170036.170072"},{"key":"2181_CR3","doi-asserted-by":"crossref","unstructured":"Amphawan K, Lenca P, Surarerks A (2009) Mining top-k periodic-frequent pattern from transactional databases without support threshold. In: Proceedings of the 3rd international conference on advances in information technology, pp 18\u201329","DOI":"10.1007\/978-3-642-10392-6_3"},{"key":"2181_CR4","doi-asserted-by":"crossref","unstructured":"Amphawan K, Surarerks A, Lenca P (2010) Mining periodic-frequent itemsets with approximate periodicity using interval transaction-ids list tree. In: Proceedings of the 3rd international conference on knowledge discovery and data mining, pp 245\u2013248","DOI":"10.1109\/WKDD.2010.126"},{"key":"2181_CR5","doi-asserted-by":"crossref","unstructured":"Bodon F, Schmidt-Thieme L (2005) The relation of closed itemset mining, complete pruning strategies and item ordering in apriori-based FIM algorithms. In: Proceedings of the 9th European conference on principles and practice of knowledge discovery in databases. ACM, pp 437\u2013444","DOI":"10.1007\/11564126_43"},{"issue":"439","key":"2181_CR6","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.ins.2018.01.046","volume":"1","author":"KW Chon","year":"2018","unstructured":"Chon KW, Hwang SH, Kim MS (2018) GMiner: a fast GPU-based frequent itemset mining method for large-scale data. Inform Sci 1(439):19\u201338","journal-title":"Inform Sci"},{"key":"2181_CR7","unstructured":"Cormen TH, Leiserson CE, Rivest RL, Stein C (2009) Introduction to algorithms. MIT press"},{"key":"2181_CR8","doi-asserted-by":"crossref","unstructured":"Dinh DT, Le B, Fournier-Viger P, Huynh VN (2018) An efficient algorithm for mining periodic high-utility sequential patterns. Appl Intell 48(12):4694\u20134714","DOI":"10.1007\/s10489-018-1227-x"},{"issue":"2","key":"2181_CR9","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1109\/TCE.2011.5955246","volume":"57","author":"ACM Fong","year":"2011","unstructured":"Fong ACM, Zhou B, Hui SC, Hong GY, Do T (2011) Web content recommender system based on consumer behavior modeling. IEEE Trans Consum Electron 57(2):962\u2013969","journal-title":"IEEE Trans Consum Electron"},{"issue":"1","key":"2181_CR10","first-page":"3389","volume":"15","author":"P Fournier-Viger","year":"2014","unstructured":"Fournier-Viger P, Gomariz A, Gueniche T, Soltani A, Wu C, Tseng VS (2014) SPMF: a Java open-source pattern mining library. J Mach Learn Res 15(1):3389\u20133393","journal-title":"J Mach Learn Res"},{"key":"2181_CR11","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Lin JCW, Duong QH, Dam TL, Sevcik L, Uhrin D, Voznak M (2017) PFPM: discovering periodic frequent patterns with novel periodicity measures. In: Proceedings of the 2nd Czech-China scientific conference 2016. IntechOpen","DOI":"10.5772\/66780"},{"key":"2181_CR12","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Lin JCW, Duong QH, Dam TL (2016) PHM: mining periodic high-utility itemsets. In: Proceedings of the industrial conference on data mining, pp 64\u201379","DOI":"10.1007\/978-3-319-41561-1_6"},{"issue":"1","key":"2181_CR13","first-page":"54","volume":"1","author":"P Fournier-Viger","year":"2017","unstructured":"Fournier-Viger P, Lin JCW, Kiran RU, Koh YS, Thomas R (2017) A survey of sequential pattern mining. Data Sci Pattern Recogn 1(1):54\u201377","journal-title":"Data Sci Pattern Recogn"},{"key":"2181_CR14","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Lin JCW, Truong-Chi T, Nkambou R (2019) A survey of high utility itemset mining. In: High-utility pattern mining. Springer, Cham, pp 1\u201345","DOI":"10.1007\/978-3-030-04921-8_1"},{"key":"2181_CR15","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Lin JCW, Vo B, Truong TC, Zhang J, Le HB (2017) A survey of itemset mining. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7(4):e1207","DOI":"10.1002\/widm.1207"},{"key":"2181_CR16","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Li Z, Lin JCW, Kiran RU, Fujita H (2018) Discovering periodic patterns common to multiple sequences. In: Proceedings of the 20th international conference on data warehousing and knowledge discovery. Regensburg: Springer, pp 231\u2013246","DOI":"10.1007\/978-3-319-98539-8_18"},{"key":"2181_CR17","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Yang P, Lin JCW, Kiran RU (2019) Discovering stable periodic-frequent patterns in transactional data. In: Proceedings of the 32nd international conference on industrial, engineering and other applications of applied intelligent systems. Springer, pp 230\u2013244","DOI":"10.1007\/978-3-030-22999-3_21"},{"key":"2181_CR18","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Wu CW, Zida S, Tseng VS (2014) FHM: faster high-utility itemset mining using estimated utility co-occurrence pruning. In: Proceedings of the 21st international symposium on methodologies for intelligent systems, pp 83\u201392","DOI":"10.1007\/978-3-319-08326-1_9"},{"key":"2181_CR19","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Yang P, Lin C, Yun U (2019) HUE-Span: fast high utility episode mining. In: Proceedings of the 14th international conference on advanced data mining and applications, pp 169\u2013184","DOI":"10.1007\/978-3-030-35231-8_12"},{"issue":"4","key":"2181_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2523813","volume":"46","author":"J Gama","year":"2014","unstructured":"Gama J, Zliobaite I, Bifet A, Pechenizkiy M, Bouchachia H (2014) A survey on concept drift adaptation. J ACM Comput Surv 46(4):1\u201337","journal-title":"J ACM Comput Surv"},{"key":"2181_CR21","doi-asserted-by":"crossref","unstructured":"Gouda K, Zaki MJ (2001) Efficiently mining maximal frequent itemsets. In: Proceedings of the 17th IEEE international conference on data mining. ACM, pp 163\u2013170","DOI":"10.1109\/ICDM.2001.989514"},{"issue":"10","key":"2181_CR22","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1109\/TKDE.2005.166","volume":"17","author":"G Grahne","year":"2005","unstructured":"Grahne G, Zhu J (2005) Fast algorithms for frequent itemset mining using fp-trees. IEEE Trans Knowl Data Eng 17(10):1347\u20131362","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"1","key":"2181_CR23","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1023\/B:DAMI.0000005258.31418.83","volume":"8","author":"J Han","year":"2000","unstructured":"Han J, Pei J, Yin Y, Mao R (2000) Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Mining Knowl Discov 8(1):53\u201387","journal-title":"Data Mining Knowl Discov"},{"key":"2181_CR24","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.is.2007.07.003","volume":"33","author":"K Huang","year":"2008","unstructured":"Huang K, Chang C (2008) Efficient mining of frequent episodes from complex sequences. Inf Syst 33:96\u2013114","journal-title":"Inf Syst"},{"key":"2181_CR25","doi-asserted-by":"crossref","unstructured":"Huang Y, Hsu CL, Tseng VS (2020) PURL: periodic user representation learning from temporal event records for personalized health management. In: Proceedings of the 7th IEEE international conference on big data and smart computing. IEEE, pp 358\u2013365","DOI":"10.1109\/BigComp48618.2020.00-49"},{"key":"2181_CR26","doi-asserted-by":"crossref","unstructured":"Islam MA, Acharjee UK (2020) Mining periodic patterns and accuracy calculation for activity monitoring using RF tag arrays. In: Proceedings of the international joint conference on computational intelligence. Springer, pp 85\u201395","DOI":"10.1007\/978-981-13-7564-4_8"},{"key":"2181_CR27","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.jss.2015.10.035","volume":"112","author":"RU Kiran","year":"2016","unstructured":"Kiran RU, Kitsuregawa M, Reddy PK (2016) Efficient discovery of periodic-frequent patterns in very large databases. J Syst Softw 112:110\u2013121","journal-title":"J Syst Softw"},{"key":"2181_CR28","unstructured":"Kiran RU, Reddy PK (2010) Mining rare periodic-frequent patterns using multiple minimum supports. In: Proceedings of the 15th international conference on management of data, pp 7\u20138"},{"key":"2181_CR29","doi-asserted-by":"crossref","unstructured":"Kiran RU, Saideep C, Zettsu K, Toyoda M, Kitsuregawa M, Reddy PK (2019) Discovering partial periodic spatial patterns in spatiotemporal databases. In: Proceedings of the 2019 IEEE international conference on big data. IEEE, pp 233\u2013238","DOI":"10.1109\/FUZZ48607.2020.9177579"},{"key":"2181_CR30","doi-asserted-by":"crossref","unstructured":"Kiran RU, Venkatesh JN, Fournier-Viger P, Toyoda M, Reddy PK, Kitsuregawa M (2017) Discovering periodic patterns in non-uniform temporal databases. In: Proceedings of the 21th Pacific-Asia conference on knowledge discovery and data mining, vol 2, pp 604\u2013617","DOI":"10.1007\/978-3-319-57529-2_47"},{"issue":"4","key":"2181_CR31","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1145\/2898359","volume":"10","author":"YS Koh","year":"2016","unstructured":"Koh YS, Ravana SD (2016) Unsupervised rare pattern mining: a survey. ACM Trans Knowl Discov Data 10(4):45","journal-title":"ACM Trans Knowl Discov Data"},{"issue":"2","key":"2181_CR32","first-page":"1506","volume":"5","author":"V Kumar","year":"2013","unstructured":"Kumar V, Valli Kumari V (2013) Incremental mining for regular frequent patterns in vertical format. Int J Eng Tech 5(2):1506\u20131511","journal-title":"Int J Eng Tech"},{"issue":"6","key":"2181_CR33","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.3233\/IDA-184255","volume":"23","author":"H Li","year":"2019","unstructured":"Li H, Hai M, Zhang N, Zhu J, Wang Y, Cao H (2019) Probabilistic maximal frequent itemset mining methods over uncertain databases. Intell Data Analy 23(6):1219\u20131241","journal-title":"Intell Data Analy"},{"issue":"6","key":"2181_CR34","doi-asserted-by":"crossref","first-page":"e1329","DOI":"10.1002\/widm.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 Knowl Discov Wiley 9(6):e1329","journal-title":"WIREs Data Mining Knowl Discov Wiley"},{"key":"2181_CR35","doi-asserted-by":"crossref","unstructured":"Manku GS (2016) Frequent itemset mining over data streams. In: Data stream management. Springer, Berlin, pp 209\u2013219","DOI":"10.1007\/978-3-540-28608-0_10"},{"key":"2181_CR36","unstructured":"Mannila H, Toivonen H, Verkamo AI (1995) Discovering frequent episodes in sequences. In: Proceedings of the first international conference on knowledge discovery and data mining, pp 210\u2013215"},{"key":"2181_CR37","doi-asserted-by":"crossref","unstructured":"Muthukrishnan S, Berg EVD, Wu Y (2007) Sequential change detection on data streams. In: Proceedings of the 7th IEEE intern. conf. on data mining workshops, pp 551\u2013550","DOI":"10.1109\/ICDMW.2007.89"},{"key":"2181_CR38","doi-asserted-by":"crossref","unstructured":"Nofong VM (2015) Discovering productive periodic frequent patterns in transactional databases. In: Proceedings of the second international conference on data science, pp 141\u2013150","DOI":"10.1007\/978-3-319-24474-7_20"},{"key":"2181_CR39","doi-asserted-by":"crossref","unstructured":"Nofong VM (2018) Fast and memory efficient mining of periodic frequent patterns. In: Proceedings of the 10th Asian conference onmodern approaches for intelligent information and database systems, pp 223\u2013232","DOI":"10.1007\/978-3-319-76081-0_19"},{"key":"2181_CR40","doi-asserted-by":"crossref","unstructured":"Pasquier N, Bastide Y, Taouil R, Lakhal L (1999) Discovering frequent closed itemsets for association rules. In: Proceedings of the 7th international conference on database theory. ACM, pp 398\u2013416","DOI":"10.1007\/3-540-49257-7_25"},{"key":"2181_CR41","doi-asserted-by":"crossref","unstructured":"Rashid MM, Gondal I, Kamruzzaman J (2013) Regularly frequent patterns mining from sensor data stream. In: Proceedings of the 20th international conference on neural information processing, pp 417\u2013424","DOI":"10.1007\/978-3-642-42042-9_52"},{"key":"2181_CR42","doi-asserted-by":"crossref","unstructured":"Rashid MM, Karim MR, Jeong BS, Choi HJ (2012) Efficient mining regularly frequent patterns in transactional databases. In: Proceedings of the 17th international conference on database systems for advanced applications, pp 258\u2013271","DOI":"10.1007\/978-3-642-29038-1_20"},{"key":"2181_CR43","doi-asserted-by":"crossref","unstructured":"Surana A, Kiran RU, Reddy PK (2012) An efficient approach to mine periodic-frequent patterns in transactional databases. In: Proceedings of the 16th Pacific-Asia conference on knowledge discovery and data mining, pp 254\u2013266","DOI":"10.1007\/978-3-642-28320-8_22"},{"key":"2181_CR44","doi-asserted-by":"crossref","unstructured":"Tanbeer SK, Ahmed CF, Jeong BS, Lee YK (2009) Discovering periodic-frequent patterns in transactional databases. In: Proceedings of the 13rd Pacific-Asia conference on knowledge discovery and data mining, pp 242\u2013253","DOI":"10.1007\/978-3-642-01307-2_24"},{"issue":"4","key":"2181_CR45","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1007\/s11390-015-1555-9","volume":"30","author":"YX Tong","year":"2015","unstructured":"Tong YX, Chen L, She J (2015) Mining frequent itemsets in correlated uncertain databases. J Comput Sci Technol 30(4):696\u2013712","journal-title":"J Comput Sci Technol"},{"key":"2181_CR46","doi-asserted-by":"crossref","unstructured":"Truong-Chi T, Fournier-Viger P (2019) A survey of high utility sequential pattern mining. In: High-utility pattern mining. Springer, Cham, pp 97\u2013129","DOI":"10.1007\/978-3-030-04921-8_4"},{"key":"2181_CR47","doi-asserted-by":"crossref","unstructured":"Wong MH, Tseng VS, Tseng JC, Liu SW, Tsai CH (2017) Long-term user location prediction using deep learning and periodic pattern mining. In: Proceedings of the 12th International conference on advanced data mining and applications, pp 582\u2013594","DOI":"10.1007\/978-3-319-69179-4_41"},{"key":"2181_CR48","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.knosys.2017.12.029","volume":"144","author":"U Yun","year":"2018","unstructured":"Yun U, Kim D, Yoon E, Fujita H (2018) Damped window based high average utility pattern mining over data streams. Knowl-Based Syst 144:188\u2013205","journal-title":"Knowl-Based Syst"},{"issue":"9","key":"2181_CR49","doi-asserted-by":"publisher","first-page":"7239","DOI":"10.1109\/TIE.2017.2682782","volume":"64","author":"U Yun","year":"2017","unstructured":"Yun U, Lee G, Yoon E (2017) Efficient high utility pattern mining for establishing manufacturing plans with sliding window control. IEEE Trans Industr Electron 64(9):7239\u20137249","journal-title":"IEEE Trans Industr Electron"},{"key":"2181_CR50","doi-asserted-by":"crossref","unstructured":"Zaki MJ, Gouda K (2003) Fast vertical mining using diffsets. In: Proceedings of the 9th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 326\u2013335","DOI":"10.1145\/956750.956788"},{"issue":"2","key":"2181_CR51","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1007\/s11227-017-2049-z","volume":"6","author":"R Zhang","year":"2019","unstructured":"Zhang R, Chen W, Hsu TC, Yang H, Chung YC (2019) ANG: a combination of Apriori and graph computing techniques for frequent itemsets mining. J Supercomput 6(2):646\u201361","journal-title":"J Supercomput"},{"key":"2181_CR52","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.eswa.2018.12.047","volume":"122","author":"D Zhang","year":"2019","unstructured":"Zhang D, Lee K, Lee I (2019) Mining hierarchical semantic periodic patterns from GPS-collected spatio-temporal trajectories. Exp Syst Applic 122:85\u2013101","journal-title":"Exp Syst Applic"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-02181-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-020-02181-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-02181-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T03:10:55Z","timestamp":1697771455000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-020-02181-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,3]]},"references-count":52,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["2181"],"URL":"https:\/\/doi.org\/10.1007\/s10489-020-02181-6","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,3]]},"assertion":[{"value":"26 December 2020","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 February 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest and competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of interests"}}]}}