{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:24:21Z","timestamp":1740122661549,"version":"3.37.3"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"13","license":[{"start":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T00:00:00Z","timestamp":1647302400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T00:00:00Z","timestamp":1647302400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["Grant 61672261 and Grant 61802056"],"award-info":[{"award-number":["Grant 61672261 and Grant 61802056"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"industrial technology research and development project of jilin development and reform commission","award":["Grant 2019C053-9"],"award-info":[{"award-number":["Grant 2019C053-9"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s10489-022-03186-z","type":"journal-article","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T23:02:21Z","timestamp":1647385341000},"page":"15387-15404","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Discovering periodic cluster patterns in event sequence databases"],"prefix":"10.1007","volume":"52","author":[{"given":"Guisheng","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1648-8138","authenticated-orcid":false,"given":"Zhanshan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,15]]},"reference":[{"key":"3186_CR1","doi-asserted-by":"crossref","unstructured":"Zhang R, Huang Y, Pu M, Zhang J, Ling H (2020) Object discovery from a single unlabeled image by mining frequent itemsets with multi-scale features. IEEE Transactions on Image Processing. PP(99) 1\u20131","DOI":"10.1109\/TIP.2020.3015543"},{"key":"3186_CR2","doi-asserted-by":"publisher","first-page":"103664","DOI":"10.1016\/j.engappai.2020.103664","volume":"92","author":"G Soleimani","year":"2020","unstructured":"Soleimani G, Abessi M (2020) DLCSS: A new similarity measure for time series data mining. Eng Appl Artif Intell 92:103664","journal-title":"Eng Appl Artif Intell"},{"issue":"31","key":"3186_CR3","doi-asserted-by":"publisher","first-page":"2605","DOI":"10.1007\/s00521-017-3217-z","volume":"2019","author":"H Zhou","year":"2019","unstructured":"Zhou H, Hirasawa K (2019) Evolving temporal association rules in recommender system. Neural Comput & Applic 2019(31):2605\u20132619","journal-title":"Neural Comput & Applic"},{"key":"3186_CR4","doi-asserted-by":"crossref","unstructured":"Mabu AM, Prasad R, Yadav R, Jauro SS (2018) A Review of Data Mining Methods in Bioinformatics. 2018 Recent Advances on Engineering, Technology and Computational Sciences (RAETCS)","DOI":"10.1109\/RAETCS.2018.8443785"},{"issue":"2","key":"3186_CR5","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1145\/170036.170072","volume":"22","author":"R Agrawal","year":"1993","unstructured":"Agrawal R, Imieli\u0144ski T, Swami A (1993) Mining association rules between sets of items in large databases. ACM SIGMOD Rec 22(2):207\u2013216","journal-title":"ACM SIGMOD Rec"},{"key":"3186_CR6","doi-asserted-by":"publisher","unstructured":"Islam MA, Rafi MR, Azad AA, Ovi JA (2021) Weighted frequent sequential pattern mining. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-021-02290-w","DOI":"10.1007\/s10489-021-02290-w"},{"key":"3186_CR7","doi-asserted-by":"publisher","unstructured":"Van T, Le B (2021) Mining sequential rules with itemset constraints. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-020-02153-w","DOI":"10.1007\/s10489-020-02153-w"},{"issue":"Mar.","key":"3186_CR8","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.jss.2016.11.035","volume":"125","author":"RU Kiran","year":"2017","unstructured":"Kiran RU, Venkatesh JN, Toyoda M, Kitsuregawa M, Reddy PK (2017) Discovering partial periodic-frequent patterns in a transactional database. J Syst Softw 125(Mar.):170\u2013182","journal-title":"J Syst Softw"},{"key":"3186_CR9","doi-asserted-by":"publisher","first-page":"103933","DOI":"10.1016\/j.engappai.2020.103933","volume":"96","author":"KK Sethi","year":"2020","unstructured":"Sethi KK, Ramesh D (2020) High average-utility itemset mining with multiple minimum utility threshold: a generalized approach. Eng Appl Artif Intell 96:103933","journal-title":"Eng Appl Artif Intell"},{"issue":"Apr.","key":"3186_CR10","first-page":"103539.1","volume":"90","author":"L Nguyen","year":"2020","unstructured":"Nguyen L, Vo B, Le NT, Snasel V, Zelinka I (2020) Fast and scalable algorithms for mining subgraphs in a single large graph. Eng Appl Artif Intell 90(Apr.):103539.1\u2013103539.12","journal-title":"Eng Appl Artif Intell"},{"key":"3186_CR11","doi-asserted-by":"publisher","unstructured":"Kanaan M, Cazabet R, Kheddouci H (2020) Temporal Pattern Mining for Ecommerce Dataset. In: Transactions on large-scale data- and knowledge-centered systems XLVI, Springer Berlin Heidelberg, Berlin, Heidelberg, 2020, pp. 67\u201390. https:\/\/doi.org\/10.1007\/978-3-662-62386-2_3","DOI":"10.1007\/978-3-662-62386-2_3"},{"key":"3186_CR12","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.engappai.2015.04.014","volume":"44","author":"AK Chanda","year":"2015","unstructured":"Chanda AK, Saha S, Nishi MA, Samiullah M, Ahmed CF (2015) An efficient approach to mine flexible periodic patterns in time series databases. Eng Appl Artif Intell. (2015) 44:46\u201363","journal-title":"Eng Appl Artif Intell. (2015)"},{"key":"3186_CR13","first-page":"617","volume":"2017","author":"Q Yuan","year":"2017","unstructured":"Yuan Q, Shang J, Cao X, Zhang C, Geng X, Han J (2017) Detecting multiple periods and periodic patterns in event time sequences. CIKM 2017:617\u2013626","journal-title":"CIKM"},{"key":"3186_CR14","first-page":"85","volume":"2015","author":"J Kostrzewa","year":"2015","unstructured":"Kostrzewa J (2015) Time series forecasting using clustering with periodic pattern. IJCCI (NCTA) 2015:85\u201392","journal-title":"IJCCI (NCTA)"},{"key":"3186_CR15","first-page":"242","volume":"2009","author":"SK Tanbeer","year":"2009","unstructured":"Tanbeer SK, Ahmed CF, Jeong B, Lee Y (2009) Discovering Periodic-Frequent patterns in transactional databases. PAKDD 2009:242\u2013253","journal-title":"PAKDD"},{"key":"3186_CR16","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Lin CW, Duong QH, Dam TL, Voznak M (2016) PFPM: Discovering periodic frequent patterns with novel periodicity measures. In: Proceedings of the 2nd Czech-China scientific conference, 2016, 2017","DOI":"10.5772\/66780"},{"key":"3186_CR17","doi-asserted-by":"crossref","unstructured":"Rana S, Mondal MNI (2021) An approach for seasonally periodic frequent pattern mining in retail supermarket. SSRN Electronic Journal 2021;(1)","DOI":"10.2139\/ssrn.3852739"},{"issue":"5","key":"3186_CR18","first-page":"1219","volume":"27","author":"Z Li","year":"2015","unstructured":"Li Z, Wang J, Han J (2015) ePeriodicity:, Mining event periodicity from incomplete observations. TKDE (2015) 27(5):1219\u2013 1232","journal-title":"TKDE (2015)"},{"key":"3186_CR19","first-page":"226","volume":"1996","author":"M Ester","year":"1996","unstructured":"Ester M, Kriegel H, Sander J, Xu X (1996) A Density-Based algorithm for discovering clusters in large spatial databases with noise. KDD 1996:226\u2013231","journal-title":"KDD"},{"key":"3186_CR20","doi-asserted-by":"publisher","unstructured":"Cumby CM, Fano AE, Ghani R, Krema M (2004) Predicting customer shopping lists from point-of-sale purchase data. In: Proceedings of the Tenth ACM SIGKDD international conference on knowledge discovery and data mining, pp 402\u2013409. https:\/\/doi.org\/10.1145\/1014052.1014098","DOI":"10.1145\/1014052.1014098"},{"issue":"10","key":"3186_CR21","doi-asserted-by":"publisher","first-page":"4232","DOI":"10.1016\/j.eswa.2013.01.021","volume":"40","author":"KJ Yang","year":"2013","unstructured":"Yang KJ, Hong TP, Chen YM, Lan GC (2013) Projection-based partial periodic pattern mining for event sequences. Expert Syst Appl 40(10):4232\u20134240","journal-title":"Expert Syst Appl"},{"key":"3186_CR22","doi-asserted-by":"crossref","unstructured":"Amphawan K, Lenca P, Surarerks A (2009) Mining Top-K Periodic-Frequent pattern from transactional databases without support threshold. IAIT, pp 18\u201329","DOI":"10.1007\/978-3-642-10392-6_3"},{"key":"3186_CR23","first-page":"183","volume":"1","author":"RU Kiran","year":"2011","unstructured":"Kiran RU, Reddy PK (2011) An alternative interestingness measure for mining Periodic-Frequent patterns. DASFAA 1:183\u2013192","journal-title":"DASFAA"},{"key":"3186_CR24","first-page":"258","volume":"1","author":"MM Rashid","year":"2012","unstructured":"Rashid MM, Karim MR, Jeong BS, Choi HJ (2012) Efficient mining regularly frequent patterns in transactional databases. DASFAA 1:258\u2013271","journal-title":"DASFAA"},{"key":"3186_CR25","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":"3186_CR26","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, Kiran RU, Fujita H (2019) Efficient algorithms to identify periodic patterns in multiple sequences. Inf Sci 489:205\u2013226. https:\/\/doi.org\/10.1016\/j.ins.2019.03.050","journal-title":"Inf Sci"},{"key":"3186_CR27","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.ins.2020.09.044","volume":"544","author":"P Fournier-Viger","year":"2021","unstructured":"Fournier-Viger P, Yang P, Kiran RU, Ventura S, Luna JM (2021) Mining local periodic patterns in a discrete sequence. Inf Sci 544:519\u2013548","journal-title":"Inf Sci"},{"key":"3186_CR28","doi-asserted-by":"crossref","unstructured":"Fournier-Viger P, Wang Y, Yang P, Lin CW, Kiran RU (2021) TSPIN: mining top-k stable periodic patterns. Applied Intelligence(439)","DOI":"10.1007\/s10489-020-02181-6"},{"key":"3186_CR29","doi-asserted-by":"crossref","unstructured":"Nofong VM (2018) Fast and memory efficient mining of periodic frequent patterns, vol 2018","DOI":"10.1007\/978-3-319-76081-0_19"},{"key":"3186_CR30","unstructured":"Ma S, Hellerstein JL (2001) Mining partially periodic event patterns with unknown periods. ICDE, pp 205\u2013214"},{"key":"3186_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.engappai.2017.11.005","volume":"69","author":"S Akther","year":"2018","unstructured":"Akther S, Karim MR, Samiullah M, Ahmed CF (2018) Mining non-redundant closed flexible periodic patterns. Eng Appl Artif Intell 69:1\u201323","journal-title":"Eng Appl Artif Intell"},{"key":"3186_CR32","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. IEEE BigData, pp 233\u2013238","DOI":"10.1145\/3335783.3335789"},{"key":"3186_CR33","first-page":"321","volume":"1","author":"MK Afriyie","year":"2020","unstructured":"Afriyie MK, Nofong VM, Wondoh J, Abdel-Fatao H (2020) Mining Non-redundant Periodic Frequent Patterns. ACIIDS 1:321\u2013331","journal-title":"ACIIDS"},{"key":"3186_CR34","doi-asserted-by":"publisher","first-page":"1225","DOI":"10.1007\/s10618-021-00753-9","volume":"35","author":"JW Huang","year":"2021","unstructured":"Huang JW, Jaysawal BP, Wang CC (2021) Mining full, inner and tail periodic patterns with perfect, imperfect and asynchronous periodicity simultaneously. Data Min Knowl Disc 35:1225\u20131257. https:\/\/doi.org\/10.1007\/s10618-021-00753-9","journal-title":"Data Min Knowl Disc"},{"issue":"1","key":"3186_CR35","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1140\/epjds\/s13688-018-0133-0","volume":"7","author":"R Guidotti","year":"2018","unstructured":"Guidotti R, Gabrielli L, Monreale A, Pedreschi D, Giannotti F (2018) Discovering temporal regularities in retail customers\u2019 shopping behavior. Epj Data Science 7(1):6","journal-title":"Epj Data Science"},{"issue":"11","key":"3186_CR36","doi-asserted-by":"publisher","first-page":"2151","DOI":"10.1109\/TKDE.2018.2872587","volume":"31","author":"R Guidotti","year":"2019","unstructured":"Guidotti R, Rossetti G, Pappalardo L, Giannotti F, Pedreschi D (2019) Personalized market basket prediction with temporal annotated recurring sequences. IEEE Trans Knowl Data Eng 31(11):2151\u20132163. https:\/\/doi.org\/10.1109\/TKDE.2018.2872587","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3186_CR37","unstructured":"Lee DD, Seung HS (2000) Algorithms for non-negative matrix factorization. In: Advances in neural information processing systems 13, papers from neural information processing systems (NIPS), vol 2000, pp 556\u2013562"},{"key":"3186_CR38","doi-asserted-by":"publisher","unstructured":"Wang P, Guo J, Lan Y, Xu J, Wan S, Cheng X (2015) Learning hierarchical representation model for next basket recommendation. In: Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval, pp 403\u2013412. https:\/\/doi.org\/10.1145\/2766462.2767694","DOI":"10.1145\/2766462.2767694"},{"key":"3186_CR39","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1145\/3397271.3401066","volume":"2020","author":"HJ Hu","year":"2020","unstructured":"Hu HJ, He XN, Gao JY, Zhang ZL (2020) Modeling Personalized Item Frequency Information for Next-basket Recommendation. SIGIR 2020:1071\u20131080","journal-title":"SIGIR"},{"key":"3186_CR40","doi-asserted-by":"publisher","unstructured":"Faggioli G, Polato M, Aiolli F (2020) Recency aware collaborative filtering for next basket recommendation. In: UMAP\u201920, July. https:\/\/doi.org\/10.1145\/3340631.3394850, vol 14-17. Genoa, Italy, pp 80\u201387","DOI":"10.1145\/3340631.3394850"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03186-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03186-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03186-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T10:02:15Z","timestamp":1664618535000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03186-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,15]]},"references-count":40,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["3186"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03186-z","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2022,3,15]]},"assertion":[{"value":"31 December 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 March 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":"We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}