{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T23:11:36Z","timestamp":1778973096426,"version":"3.51.4"},"reference-count":188,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2021,1,26]],"date-time":"2021-01-26T00:00:00Z","timestamp":1611619200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,26]],"date-time":"2021-01-26T00:00:00Z","timestamp":1611619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1007\/s10489-020-02160-x","type":"journal-article","created":{"date-parts":[[2021,1,26]],"date-time":"2021-01-26T23:02:40Z","timestamp":1611702160000},"page":"6029-6055","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":84,"title":["A survey for user behavior analysis based on machine learning techniques: current models and applications"],"prefix":"10.1007","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0257-3764","authenticated-orcid":false,"given":"Alejandro","family":"G. Mart\u00edn","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0848-1190","authenticated-orcid":false,"given":"Alberto","family":"Fern\u00e1ndez-Isabel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5197-2932","authenticated-orcid":false,"given":"Isaac","family":"Mart\u00edn de Diego","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1689-7479","authenticated-orcid":false,"given":"Marta","family":"Beltr\u00e1n","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,26]]},"reference":[{"key":"2160_CR1","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.jnca.2016.04.007","volume":"68","author":"A Abdallah","year":"2016","unstructured":"Abdallah A, Maarof MA, Zainal A (2016) Fraud detection system: a survey. J Netw Comput Appl 68:90\u2013113","journal-title":"J Netw Comput Appl"},{"key":"2160_CR2","doi-asserted-by":"crossref","unstructured":"Afridi MW, Ali T, Alghamdi T, Ali T, Yasar M (2018) Android application behavioral analysis through intent monitoring. In: 2018 6th International symposium on digital forensic and security (ISDFS). IEEE, pp 1\u20138","DOI":"10.1109\/ISDFS.2018.8355359"},{"issue":"3","key":"2160_CR3","doi-asserted-by":"publisher","first-page":"399","DOI":"10.3182\/20060517-3-FR-2903.00211","volume":"39","author":"B Agard","year":"2006","unstructured":"Agard B, Morency C, Tr\u00e9panier M (2006) Mining public transport user behaviour from smart card data. IFAC Proc 39(3):399\u2013404","journal-title":"IFAC Proc"},{"issue":"1","key":"2160_CR4","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1016\/S0386-1112(14)60232-6","volume":"33","author":"T Akiyama","year":"2009","unstructured":"Akiyama T, Okushima M (2009) Analysis of railway user travel behaviour patterns of different age groups. IATSS Res 33(1):6\u201317","journal-title":"IATSS Res"},{"issue":"2","key":"2160_CR5","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s00779-014-0823-y","volume":"19","author":"H Alemdar","year":"2015","unstructured":"Alemdar H, Tunca C, Ersoy C (2015) Daily life behaviour monitoring for health assessment using machine learning: bridging the gap between domains. Pers Ubiquit Comput 19(2):303\u2013315","journal-title":"Pers Ubiquit Comput"},{"key":"2160_CR6","doi-asserted-by":"crossref","unstructured":"Alieksieiev V, Strelnitskiy A, Gavva D, Gorelov D, Synytsia Y (2018) Studying of keystroke dynamics statistical properties for biometrie user authentication. In: 2018 14th International conference on advanced trends in radioelecrtronics, telecommunications and computer engineering (TCSET). IEEE, pp 559\u2013563","DOI":"10.1109\/TCSET.2018.8336264"},{"key":"2160_CR7","doi-asserted-by":"crossref","unstructured":"Alimolaei S (2015) An intelligent system for user behavior detection in internet banking. In: 2015 4th Iranian joint congress on fuzzy and intelligent systems (CFIS). IEEE, pp 1\u20135","DOI":"10.1109\/CFIS.2015.7391642"},{"key":"2160_CR8","doi-asserted-by":"crossref","unstructured":"Aljohani O, Aljohani N, Bours P, Alsolami F (2018) Continuous authentication on PCs using artificial immune system. In: 2018 1St international conference on computer applications & information security (ICCAIS). IEEE, pp 1\u20136","DOI":"10.1109\/CAIS.2018.8442022"},{"key":"2160_CR9","unstructured":"Allen Institute for Artificial Intelligence (2015) Semantic scholar. https:\/\/www.semanticscholar.org\/, [Online: accessed 08-Sept-2020]"},{"key":"2160_CR10","doi-asserted-by":"crossref","unstructured":"Anguita D, Ghio A, Oneto L, Parra X, Reyes-Ortiz JL (2012) Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine. In: International workshop on ambient assisted living. Springer, pp 216\u2013223","DOI":"10.1007\/978-3-642-35395-6_30"},{"issue":"2","key":"2160_CR11","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1109\/TITS.2017.2700869","volume":"19","author":"N Arbabzadeh","year":"2017","unstructured":"Arbabzadeh N, Jafari M (2017) A data-driven approach for driving safety risk prediction using driver behavior and roadway information data. IEEE Trans Intell Transport Sys 19(2):446\u2013460","journal-title":"IEEE Trans Intell Transport Sys"},{"issue":"2","key":"2160_CR12","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1049\/iet-its.2009.0070","volume":"4","author":"I Arel","year":"2010","unstructured":"Arel I, Liu C, Urbanik T, Kohls A (2010) Reinforcement learning-based multi-agent system for network traffic signal control. IET Intell Transp Syst 4(2):128\u2013135","journal-title":"IET Intell Transp Syst"},{"issue":"3","key":"2160_CR13","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1109\/59.871739","volume":"15","author":"JM Arroyo","year":"2000","unstructured":"Arroyo JM, Conejo AJ (2000) Optimal response of a thermal unit to an electricity spot market. IEEE Trans Power Sys 15(3):1098\u20131104","journal-title":"IEEE Trans Power Sys"},{"key":"2160_CR14","doi-asserted-by":"crossref","unstructured":"Aztiria A, Izaguirre A, Basagoiti R, Augusto JC, Cook DJ (2010) Automatic modeling of frequent user behaviours in intelligent environments. In: 2010 Sixth international conference on intelligent environments (IE). IEEE, pp 7\u201312","DOI":"10.1109\/IE.2010.9"},{"issue":"12","key":"2160_CR15","doi-asserted-by":"publisher","first-page":"2271","DOI":"10.1109\/TKDE.2018.2821671","volume":"30","author":"T Bai","year":"2018","unstructured":"Bai T, Zhao W X, He Y, Nie J Y, Wen J R (2018) Characterizing and predicting early reviewers for effective product marketing on e-commerce websites. IEEE Trans Knowl Data Eng 30(12):2271\u20132284","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"4","key":"2160_CR16","first-page":"43","volume":"5","author":"P Balaji","year":"2010","unstructured":"Balaji P, Srinivasan D (2010) Multi-agent system in urban traffic signal control. IEEE Comput Intell Mag 5(4):43\u201351","journal-title":"IEEE Comput Intell Mag"},{"key":"2160_CR17","doi-asserted-by":"crossref","unstructured":"Banokin PI, Tsapko GP (2014) Architecture of software system for corporate and technological control software users\u2019 behavior analysis. In: 2014 International conference on mechanical engineering, automation and control systems (MEACS). IEEE, pp 1\u20135","DOI":"10.1109\/MEACS.2014.6986920"},{"issue":"3-4","key":"2160_CR18","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1057\/dbm.2010.21","volume":"17","author":"J Bayer","year":"2010","unstructured":"Bayer J (2010) Customer segmentation in the telecommunications industry. J Database Market Cust Strat Manag 17(3-4):247\u2013256","journal-title":"J Database Market Cust Strat Manag"},{"issue":"6","key":"2160_CR19","first-page":"114","volume":"3","author":"N Bhargava","year":"2013","unstructured":"Bhargava N, Sharma G, Bhargava R, Mathuria M (2013) Decision tree analysis on j48 algorithm for data mining. Proc Int J Adv Res Comput Sci Softw Eng 3(6):114\u20131119","journal-title":"Proc Int J Adv Res Comput Sci Softw Eng"},{"issue":"1","key":"2160_CR20","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.datak.2006.01.013","volume":"60","author":"D Birant","year":"2007","unstructured":"Birant D, Kut A (2007) ST-DBSCAN: An algorithm for clustering spatial\u2013temporal data. Data Knowl Eng 60(1):208\u2013221","journal-title":"Data Knowl Eng"},{"key":"2160_CR21","doi-asserted-by":"crossref","unstructured":"Bohge M, Trappe W (2003) An authentication framework for hierarchical ad hoc sensor networks. In: Proceedings of the 2nd ACM workshop on Wireless security. ACM, pp 79\u201387","DOI":"10.1145\/941311.941324"},{"issue":"6","key":"2160_CR22","doi-asserted-by":"publisher","first-page":"2171","DOI":"10.1109\/TITS.2018.2864637","volume":"20","author":"A Bouhoute","year":"2018","unstructured":"Bouhoute A, Oucheikh R, Boubouh K, Berrada I (2018) Advanced driving behavior analytics for an improved safety assessment and driver fingerprinting. IEEE Trans Intell Transp Syst 20(6):2171\u20132184","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"5","key":"2160_CR23","doi-asserted-by":"publisher","first-page":"11953","DOI":"10.3390\/s150511953","volume":"15","author":"STM Bourobou","year":"2015","unstructured":"Bourobou STM, Yoo Y (2015) User activity recognition in smart homes using pattern clustering applied to temporal ANN algorithm. Sensors 15(5):11953\u201311971","journal-title":"Sensors"},{"key":"2160_CR24","doi-asserted-by":"crossref","unstructured":"Brosso I, La Neve A, Bressan G, Ruggiero WV (2010) A continuous authentication system based on user behavior analysis. In: ARES\u201910 international conference on availability, reliability, and security, 2010. IEEE, pp 380\u2013385","DOI":"10.1109\/ARES.2010.63"},{"key":"2160_CR25","unstructured":"BV E (1997) ScienceDirect. https:\/\/www.sciencedirect.com\/, [Online: accessed 08-Sept-2020]"},{"key":"2160_CR26","doi-asserted-by":"crossref","unstructured":"Cai Y, Jiang H, Chen D, Huang MC (2018) Online learning classifier based behavioral biometric authentication. In: 2018 15th International conference on wearable and implantable body sensor networks (BSN). IEEE, pp 62\u201365","DOI":"10.1109\/BSN.2018.8329659"},{"issue":"4","key":"2160_CR27","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/MIS.2014.60","volume":"29","author":"L Cao","year":"2014","unstructured":"Cao L, Joachims T, Wang C, Gaussier E, Li J, Ou Y, Luo D, Zafarani R, Liu H, Xu G et al (2014) Behavior informatics: a new perspective. IEEE Intell Syst 29(4):62\u201380","journal-title":"IEEE Intell Syst"},{"issue":"6","key":"2160_CR28","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/MIS.2015.105","volume":"30","author":"L Cao","year":"2015","unstructured":"Cao L, Philip SY, Kumar V (2015a) Nonoccurring behavior analytics: a new area. IEEE Intell Syst 30(6):4\u201311","journal-title":"IEEE Intell Syst"},{"issue":"1","key":"2160_CR29","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1109\/TVCG.2015.2467196","volume":"22","author":"N Cao","year":"2015","unstructured":"Cao N, Shi C, Lin S, Lu J, Lin YR, Lin CY (2015b) Targetvue: Visual analysis of anomalous user behaviors in online communication systems. IEEE Trans Visual Comput Graph 22(1):280\u2013289","journal-title":"IEEE Trans Visual Comput Graph"},{"key":"2160_CR30","doi-asserted-by":"crossref","unstructured":"Cao Z, Chi C, Hao R, Xiao Y (2008) User behavior modeling and traffic analysis of IMS presence servers. In: Global telecommunications conference, 2008. IEEE GLOBECOM 2008. IEEE, pp 1\u20135","DOI":"10.1109\/GLOCOM.2008.ECP.474"},{"key":"2160_CR31","doi-asserted-by":"publisher","DOI":"10.4324\/9780203789629","volume-title":"Human behavior in the social environment: A social systems approach","author":"I Carter","year":"2017","unstructured":"Carter I (2017) Human behavior in the social environment: A social systems approach. Routledge, Abingdon"},{"key":"2160_CR32","doi-asserted-by":"crossref","unstructured":"\u010cegan L, Filip P (2017) Advanced web analytics tool for mouse tracking and real-time data processing. In: 2017 IEEE 14th international scientific conference on informatics. IEEE, pp 431\u2013435","DOI":"10.1109\/INFORMATICS.2017.8327288"},{"issue":"3","key":"2160_CR33","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: a survey. ACM Comput Surveys (CSUR) 41(3):15","journal-title":"ACM Comput Surveys (CSUR)"},{"key":"2160_CR34","first-page":"569","volume":"12","author":"CM Chen","year":"2016","unstructured":"Chen CM, Guan DJ, Huang YZ, Ou YH (2016) Anomaly network intrusion detection using hidden Markov model. Int J Innov Comput Inform Control 12:569\u2013580","journal-title":"Int J Innov Comput Inform Control"},{"key":"2160_CR35","doi-asserted-by":"crossref","unstructured":"Chen L, Zhang Z, Liu Q, Yang L, Meng Y, Wang P (2019) A method for online transaction fraud detection based on individual behavior. In: Proceedings of the ACM turing celebration conference-China. ACM, p 119","DOI":"10.1145\/3321408.3326647"},{"key":"2160_CR36","doi-asserted-by":"publisher","first-page":"17436","DOI":"10.1109\/ACCESS.2017.2744263","volume":"5","author":"Y Chen","year":"2017","unstructured":"Chen Y, Zheng Z, Chen S, Sun L, Chen D (2017) Mining customer preference in physical stores from interaction behavior. IEEE Access 5:17436\u201317449","journal-title":"IEEE Access"},{"key":"2160_CR37","doi-asserted-by":"publisher","first-page":"113732","DOI":"10.1016\/j.apenergy.2019.113732","volume":"254","author":"YW Chung","year":"2019","unstructured":"Chung YW, Khaki B, Li T, Chu C, Gadh R (2019) Ensemble machine learning-based algorithm for electric vehicle user behavior prediction. Appl Energy 254:113732","journal-title":"Appl Energy"},{"key":"2160_CR38","doi-asserted-by":"crossref","unstructured":"Conroy NJ, Rubin VL, Chen Y (2015) Automatic deception detection: methods for finding fake news. In: Proceedings of the 78th ASIS&T annual meeting: information science with impact: research in and for the community. American Society for Information Science, p 82","DOI":"10.1002\/pra2.2015.145052010082"},{"issue":"4","key":"2160_CR39","doi-asserted-by":"publisher","first-page":"1253","DOI":"10.1137\/S0895479896305696","volume":"21","author":"L De Lathauwer","year":"2000","unstructured":"De Lathauwer L, De Moor B, Vandewalle J (2000) A multilinear singular value decomposition. SIAM J Matrix Anal Appl 21(4):1253\u20131278","journal-title":"SIAM J Matrix Anal Appl"},{"issue":"1","key":"2160_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0169-7439(99)00047-7","volume":"50","author":"R De Maesschalck","year":"2000","unstructured":"De Maesschalck R, Jouan-Rimbaud D, Massart DL (2000) The mahalanobis distance. Chemomet Intell Lab Sys 50(1):1\u201318","journal-title":"Chemomet Intell Lab Sys"},{"key":"2160_CR41","doi-asserted-by":"crossref","unstructured":"Deshpande D, Deshpande S (2017) Online user behavior: a decade\u2019s perspective. In: 2017 International conference on trends in electronics and informatics (ICEI). IEEE, pp 977\u2013984","DOI":"10.1109\/ICOEI.2017.8300854"},{"issue":"10","key":"2160_CR42","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1145\/1164394.1164398","volume":"49","author":"T Dinev","year":"2006","unstructured":"Dinev T (2006) Why spoofing is serious internet fraud. Commun ACM 49(10):76\u201382","journal-title":"Commun ACM"},{"issue":"5","key":"2160_CR43","doi-asserted-by":"publisher","first-page":"2467","DOI":"10.1109\/TITS.2015.2409174","volume":"16","author":"N Ding","year":"2015","unstructured":"Ding N, He Q, Wu C, Fetzer J (2015) Modeling traffic control agency decision behavior for multimodal manual signal control under event occurrences. IEEE Trans Intell Transp Syst 16(5):2467\u20132478","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"2160_CR44","doi-asserted-by":"crossref","unstructured":"Doll\u00e1r P, Rabaud V, Cottrell G, Belongie S (2005) Behavior recognition via sparse spatio-temporal features. In: 2nd Joint IEEE international workshop on visual surveillance and performance evaluation of tracking and surveillance, 2005. IEEE, pp 65\u201372","DOI":"10.1109\/VSPETS.2005.1570899"},{"key":"2160_CR45","doi-asserted-by":"crossref","unstructured":"Fahad LG, Tahir SF, Rajarajan M (2014) Activity recognition in smart homes using clustering based classification. In: 2014 22nd international conference on pattern recognition (ICPR). IEEE, pp 1348\u20131353","DOI":"10.1109\/ICPR.2014.241"},{"key":"2160_CR46","doi-asserted-by":"crossref","unstructured":"Faria R, Sousa J, Martins A, Lagarto J (2013) Modeling the strategic behavior of the iberian electricity market producers using time series analysis. In: 2013 10th international conference on the European energy market (EEM). IEEE, pp 1\u20135","DOI":"10.1109\/EEM.2013.6607310"},{"issue":"6","key":"2160_CR47","doi-asserted-by":"publisher","first-page":"2046","DOI":"10.1007\/s10489-018-1375-z","volume":"49","author":"S Feng","year":"2019","unstructured":"Feng S, Zhang H, Cao J, Yao Y (2019) Merging user social network into the random walk model for better group recommendation. Appl Intell 49(6):2046\u20132058","journal-title":"Appl Intell"},{"key":"2160_CR48","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez-Isabel A, Fuentes-Fern\u00e1ndez R (2011) An agent-based platform for traffic simulation. In: 6th international conference SOCO 2011 soft computing models in industrial and environmental applications. Springer, pp 505\u2013514","DOI":"10.1007\/978-3-642-19644-7_53"},{"key":"2160_CR49","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.knosys.2018.07.044","volume":"161","author":"A Fern\u00e1ndez-Isabel","year":"2018","unstructured":"Fern\u00e1ndez-Isabel A, Prieto JC, Ortega F, de Diego IM, Moguerza JM, Mena J, Galindo S, Napalkova L (2018) A unified knowledge compiler to provide support the scientific community. Knowl-Based Syst 161:157\u2013171","journal-title":"Knowl-Based Syst"},{"issue":"7","key":"2160_CR50","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1145\/2818717","volume":"59","author":"E Ferrara","year":"2016","unstructured":"Ferrara E, Varol O, Davis C, Menczer F, Flammini A (2016) The rise of social bots. Commun ACM 59(7):96\u2013104","journal-title":"Commun ACM"},{"key":"2160_CR51","doi-asserted-by":"crossref","unstructured":"Firdausi I, Erwin A, Nugroho A S, et al. (2010) Analysis of machine learning techniques used in behavior-based malware detection. In: 2010 Second international conference on advances in computing, control and telecommunication technologies (ACT). IEEE, pp 201\u2013203","DOI":"10.1109\/ACT.2010.33"},{"issue":"1","key":"2160_CR52","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1109\/TIFS.2012.2225048","volume":"8","author":"M Frank","year":"2013","unstructured":"Frank M, Biedert R, Ma E, Martinovic I, Song D (2013) Touchalytics: On the applicability of touchscreen input as a behavioral biometric for continuous authentication. IEEE Trans Inf Foren Sec 8(1):136\u2013148","journal-title":"IEEE Trans Inf Foren Sec"},{"issue":"4","key":"2160_CR53","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.3390\/s18041219","volume":"18","author":"JM de Fuentes","year":"2018","unstructured":"de Fuentes JM, Gonzalez-Manzano L, Ribagorda A (2018) Secure and usable user-in-a-context continuous authentication in smartphones leveraging non-assisted sensors. Sensors 18(4):1219","journal-title":"Sensors"},{"key":"2160_CR54","doi-asserted-by":"crossref","unstructured":"Gao Y, Ma Y, Li D (2017) Anomaly detection of malicious users\u2019 behaviors for web applications based on web logs. In: 2017 IEEE 17th international conference on communication technology (ICCT). IEEE, pp 1352\u20131355","DOI":"10.1109\/ICCT.2017.8359854"},{"key":"2160_CR55","doi-asserted-by":"crossref","unstructured":"Georgiou T, Demiris Y (2015) Predicting car states through learned models of vehicle dynamics and user behaviours 2015 IEEE intelligent vehicles symposium (IV). IEEE, pp 1240\u20131245","DOI":"10.1109\/IVS.2015.7225852"},{"key":"2160_CR56","doi-asserted-by":"publisher","DOI":"10.4324\/9781351165129","volume-title":"Simulating societies: the computer simulation of social phenomena","author":"N Gilbert","year":"2018","unstructured":"Gilbert N, Doran J (2018) Simulating societies: the computer simulation of social phenomena. Routledge, Abingdon"},{"issue":"1","key":"2160_CR57","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1109\/MITS.2014.2357038","volume":"7","author":"T Gindele","year":"2015","unstructured":"Gindele T, Brechtel S, Dillmann R (2015) Learning driver behavior models from traffic observations for decision making and planning. IEEE Intell Transp Syst Mag 7(1):69\u201379","journal-title":"IEEE Intell Transp Syst Mag"},{"key":"2160_CR58","doi-asserted-by":"crossref","unstructured":"Giri R, Choi H, Hoo KS, Rao BD (2014) User behavior modeling in a cellular network using latent dirichlet allocation. In: International conference on intelligent data engineering and automated learning. Springer, pp 36\u201344","DOI":"10.1007\/978-3-319-10840-7_5"},{"key":"2160_CR59","doi-asserted-by":"crossref","unstructured":"Giuffrida C, Majdanik K, Conti M, Bos H (2014) I sensed it was you: authenticating mobile users with sensor-enhanced keystroke dynamics. In: International conference on detection of intrusions and malware, and vulnerability assessment. Springer, pp 92\u2013111","DOI":"10.1007\/978-3-319-08509-8_6"},{"key":"2160_CR60","doi-asserted-by":"crossref","unstructured":"Gomi H, Yamaguchi S, Tsubouchi K, Sasaya N (2018) Continuous authentication system using online activities. In: 2018 17Th IEEE international conference on trust, security and privacy in computing and communications\/12th IEEE international conference on big data science and engineering (TrustCom\/BigDataSE). IEEE, pp 522\u2013532","DOI":"10.1109\/TrustCom\/BigDataSE.2018.00080"},{"issue":"2","key":"2160_CR61","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/S0165-0114(98)00403-5","volume":"120","author":"PJ Groenen","year":"2001","unstructured":"Groenen PJ, Jajuga K (2001) Fuzzy clustering with squared Minkowski distances. Fuzzy Sets Syst 120(2):227\u2013237","journal-title":"Fuzzy Sets Syst"},{"issue":"7","key":"2160_CR62","doi-asserted-by":"publisher","first-page":"1645","DOI":"10.1016\/j.future.2013.01.010","volume":"29","author":"J Gubbi","year":"2013","unstructured":"Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (iot): a vision, architectural elements, and future directions. Future Gen Comput Sys 29(7):1645\u20131660","journal-title":"Future Gen Comput Sys"},{"issue":"1","key":"2160_CR63","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1111\/1365-2656.12379","volume":"85","author":"E Gurarie","year":"2016","unstructured":"Gurarie E, Bracis C, Delgado M, Meckley TD, Kojola I, Wagner CM (2016) What is the animal doing? Tools for exploring behavioural structure in animal movements. J Anim Ecol 85(1):69\u201384","journal-title":"J Anim Ecol"},{"issue":"7","key":"2160_CR64","doi-asserted-by":"publisher","first-page":"621","DOI":"10.2165\/00002018-200730070-00010","volume":"30","author":"DJ Hand","year":"2007","unstructured":"Hand DJ (2007) Principles of data mining. Drug Saf 30(7):621\u2013622","journal-title":"Drug Saf"},{"key":"2160_CR65","volume-title":"Doing a literature review: releasing the research imagination","author":"C Hart","year":"2018","unstructured":"Hart C (2018) Doing a literature review: releasing the research imagination. Sage, Newcastle upon Tyne"},{"key":"2160_CR66","doi-asserted-by":"crossref","unstructured":"Hegazy RD, Nasr OA (2015) A user behavior based handover optimization algorithm for LTE networks. In: 2015 IEEE wireless communications and networking conference (WCNC). IEEE, pp 1255\u20131260","DOI":"10.1109\/WCNC.2015.7127649"},{"key":"2160_CR67","doi-asserted-by":"publisher","first-page":"11941","DOI":"10.1109\/ACCESS.2017.2707600","volume":"5","author":"S Hern\u00e1ndez","year":"2017","unstructured":"Hern\u00e1ndez S, \u00c1lvarez P, Fabra J, Ezpeleta J (2017) Analysis of users\u2019 behavior in structured e-commerce websites. IEEE Access 5:11941\u201311958","journal-title":"IEEE Access"},{"issue":"1","key":"2160_CR68","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1109\/TITS.2014.2326082","volume":"16","author":"B Higgs","year":"2014","unstructured":"Higgs B, Abbas M (2014) Segmentation and clustering of car-following behavior: recognition of driving patterns. IEEE Trans Intell Transp Syst 16(1):81\u201390","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"7","key":"2160_CR69","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1016\/j.knosys.2008.03.026","volume":"21","author":"CS Hilas","year":"2008","unstructured":"Hilas CS, Mastorocostas PA (2008) An application of supervised and unsupervised learning approaches to telecommunications fraud detection. Knowl-Based Syst 21(7):721\u2013726","journal-title":"Knowl-Based Syst"},{"key":"2160_CR70","doi-asserted-by":"crossref","unstructured":"Hospedales T, Gong S, Xiang T (2009) A markov clustering topic model for mining behaviour in video. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 1165\u20131172","DOI":"10.1109\/ICCV.2009.5459342"},{"key":"2160_CR71","doi-asserted-by":"crossref","unstructured":"Ibrahim A, Ouda A (2017) A hybrid-based filtering approach for user authentication. In: 2017 IEEE 30th Canadian conference on electrical and computer engineering (CCECE). IEEE, pp 1\u20135","DOI":"10.1109\/CCECE.2017.7946830"},{"key":"2160_CR72","unstructured":"Institute of Electrical and Electronics Engineers (1963) IEEE. https:\/\/ieeexplore.ieee.org\/Xplore\/home.jsp, [Online: accessed 08-Sept-2020]"},{"key":"2160_CR73","doi-asserted-by":"crossref","unstructured":"Iyer D, Mohanpurkar A, Janardhan S, Rathod D, Sardeshmukh A (2011) Credit card fraud detection using hidden markov model. In: 2011 world congress on information and communication technologies (WICT). IEEE, pp 1062\u20131066","DOI":"10.1109\/WICT.2011.6141395"},{"key":"2160_CR74","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1016\/j.jclepro.2019.04.345","volume":"229","author":"H Jahangir","year":"2019","unstructured":"Jahangir H, Tayarani H, Ahmadian A, Golkar M A, Miret J, Tayarani M, Gao HO (2019) Charging demand of plug-in electric vehicles: forecasting travel behavior based on a novel rough artificial neural network approach. J Clean Prod 229:1029\u20131044","journal-title":"J Clean Prod"},{"key":"2160_CR75","doi-asserted-by":"crossref","unstructured":"Jia D, Chen Z (2012) Traffic signal control optimization based on fuzzy neural network. In: Proceedings of 2012 international conference on measurement, information and control, vol 2. IEEE, pp 1015\u20131018","DOI":"10.1109\/MIC.2012.6273473"},{"issue":"1","key":"2160_CR76","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1109\/TNSM.2018.2800690","volume":"15","author":"H Jiang","year":"2018","unstructured":"Jiang H, Yi S, Wu L, Leung H, Wang Y, Zhou X, Chen Y, Yang L (2018) Data-driven cell zooming for large-scale mobile networks. IEEE Trans Netw Serv Manag 15(1):156\u2013168","journal-title":"IEEE Trans Netw Serv Manag"},{"issue":"7","key":"2160_CR77","doi-asserted-by":"publisher","first-page":"12285","DOI":"10.3390\/s140712285","volume":"14","author":"A Jurek","year":"2014","unstructured":"Jurek A, Nugent C, Bi Y, Wu S (2014) Clustering-based ensemble learning for activity recognition in smart homes. Sensors 14(7):12285\u201312304","journal-title":"Sensors"},{"issue":"6","key":"2160_CR78","doi-asserted-by":"publisher","first-page":"1241","DOI":"10.1007\/s10796-017-9800-0","volume":"20","author":"RP Karumur","year":"2018","unstructured":"Karumur RP, Nguyen TT, Konstan JA (2018) Personality, user preferences and behavior in recommender systems. Inf Syst Front 20(6):1241\u20131265","journal-title":"Inf Syst Front"},{"key":"2160_CR79","doi-asserted-by":"crossref","unstructured":"Kasa N, Dahbura A, Ravoori C, Adams S (2019) Improving credit card fraud detection by profiling and clustering accounts. In: 2019 Systems and information engineering design symposium (SIEDS). IEEE, pp 1\u20136","DOI":"10.1109\/SIEDS.2019.8735623"},{"key":"2160_CR80","doi-asserted-by":"crossref","unstructured":"Keralapura R, Nucci A, Zhang ZL, Gao L (2010) Profiling users in a 3g network using hourglass co-clustering. In: Proceedings of the sixteenth annual international conference on mobile computing and networking. ACM, pp 341\u2013352","DOI":"10.1145\/1859995.1860034"},{"key":"2160_CR81","unstructured":"Kirschenbaum I, Wool A (2006) How to build a low-cost, extended-range RFID skimmer. In: USENIX security symposium, vol 4. The Advanced Computing System Association"},{"key":"2160_CR82","doi-asserted-by":"crossref","unstructured":"Kolosnjaji B, Zarras A, Webster G, Eckert C (2016) Deep learning for classification of malware system call sequences. In: Australasian joint conference on artificial intelligence. Springer, pp 137\u2013149","DOI":"10.1007\/978-3-319-50127-7_11"},{"issue":"99","key":"2160_CR83","first-page":"1","volume":"15","author":"X Kong","year":"2018","unstructured":"Kong X, Li M, Tang T, Tian K, Moreira-Matias L, Xia F (2018) Shared subway shuttle bus route planning based on transport data analytics. IEEE Trans Autom Sci Eng 15(99):1\u201314","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"2160_CR84","doi-asserted-by":"crossref","unstructured":"Kuefler A, Morton J, Wheeler T, Kochenderfer M (2017) Imitating driver behavior with generative adversarial networks. In: 2017 IEEE intelligent vehicles symposium (IV). IEEE, pp 204\u2013211","DOI":"10.1109\/IVS.2017.7995721"},{"key":"2160_CR85","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-019-01495-4","volume":"49","author":"A Laishram","year":"2019","unstructured":"Laishram A, Padmanabhan V (2019) Discovery of user-item subgroups via genetic algorithm for effective prediction of ratings in collaborative filtering. Appl Intell 49:1\u201317","journal-title":"Appl Intell"},{"issue":"2","key":"2160_CR86","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TDSC.2016.2540637","volume":"15","author":"N Laleh","year":"2018","unstructured":"Laleh N, Carminati B, Ferrari E (2018) Risk assessment in social networks based on user anomalous behaviors. IEEE Trans Depend Sec Comput 15(2):295\u2013308","journal-title":"IEEE Trans Depend Sec Comput"},{"key":"2160_CR87","doi-asserted-by":"crossref","unstructured":"Lampropoulos I, Vanalme GM, Kling WL (2010) A methodology for modeling the behavior of electricity prosumers within the smart grid. In: 2010 IEEE PES innovative smart grid technologies conference europe (ISGT Europe). IEEE, pp 1\u20138","DOI":"10.1109\/ISGTEUROPE.2010.5638967"},{"issue":"6380","key":"2160_CR88","doi-asserted-by":"publisher","first-page":"1094","DOI":"10.1126\/science.aao2998","volume":"359","author":"DM Lazer","year":"2018","unstructured":"Lazer DM, Baum MA, Benkler Y, Berinsky AJ, Greenhill KM, Menczer F, Metzger MJ, Nyhan B, Pennycook G, Rothschild D et al (2018) The science of fake news. Science 359 (6380):1094\u20131096","journal-title":"Science"},{"key":"2160_CR89","doi-asserted-by":"crossref","unstructured":"Leng B, Liu J, Pan H, Zhou S, Tsinghua ZN (2015) Topic model based behaviour modeling and clustering analysis for wireless network users. In: 2015 21st Asia-Pacific conference on communications (APCC). IEEE, pp 410\u2013415","DOI":"10.1109\/APCC.2015.7412547"},{"key":"2160_CR90","volume-title":"An introduction to search engines and web navigation","author":"M Levene","year":"2011","unstructured":"Levene M (2011) An introduction to search engines and web navigation. John Wiley & Sons, Hoboken"},{"key":"2160_CR91","doi-asserted-by":"publisher","DOI":"10.4324\/9780203794067","volume-title":"Culture, behavior, and personality: An introduction to the comparative study of psychosocial adaptation","author":"RA LeVine","year":"2018","unstructured":"LeVine RA (2018) Culture, behavior, and personality: An introduction to the comparative study of psychosocial adaptation. Routledge, Abingdon"},{"key":"2160_CR92","doi-asserted-by":"crossref","unstructured":"Li Q, Wu Q, Zhu C, Zhang J, Zhao W (2019) Unsupervised user behavior representation for fraud review detection with cold-start problem. In: Pacific-Asia conference on knowledge discovery and data mining. Springer, pp 222\u2013236","DOI":"10.1007\/978-3-030-16148-4_18"},{"issue":"1","key":"2160_CR93","doi-asserted-by":"publisher","first-page":"628","DOI":"10.1109\/JIOT.2018.2851185","volume":"6","author":"Y Li","year":"2018","unstructured":"Li Y, Hu H, Zhou G (2018) Using data augmentation in continuous authentication on smartphones. IEEE Int Things J 6(1):628\u2013640","journal-title":"IEEE Int Things J"},{"key":"2160_CR94","doi-asserted-by":"publisher","first-page":"12143","DOI":"10.1109\/ACCESS.2017.2724059","volume":"5","author":"Z Li","year":"2017","unstructured":"Li Z, Wang C (2017) Modeling data transport capacity of mobile networks for mobile social services. IEEE Access 5:12143\u201312157","journal-title":"IEEE Access"},{"key":"2160_CR95","doi-asserted-by":"crossref","unstructured":"Liang W, Wu Z, Cao J, Gu J (2018) Understanding customer behavior in shopping mall from indoor tracking data. In: 2018 IEEE 22nd international conference on computer supported cooperative work in design (CSCWD). IEEE, pp 648\u2013 653","DOI":"10.1109\/CSCWD.2018.8465261"},{"key":"2160_CR96","first-page":"1","volume":"14","author":"R Lin","year":"2019","unstructured":"Lin R, Pei Z, Ye Z, Wu B, Yang G (2019) A voted based random forests algorithm for smart grid distribution network faults prediction. Enterprise Inf Sys 14:1\u201319","journal-title":"Enterprise Inf Sys"},{"key":"2160_CR97","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-019-01488-3","volume":"49","author":"G Lingam","year":"2019","unstructured":"Lingam G, Rout RR, Somayajulu D (2019) Adaptive deep q-learning model for detecting social bots and influential users in online social networks. Appl Intell 49:1\u201318","journal-title":"Appl Intell"},{"key":"2160_CR98","volume-title":"Phishing attack victims likely targets for identity theft","author":"A Litan","year":"2004","unstructured":"Litan A (2004) Phishing attack victims likely targets for identity theft. Gartner Research, Stamford,"},{"key":"2160_CR99","unstructured":"Litan A, Nicolett M (2014) Market guide for user behavior analytics"},{"key":"2160_CR100","doi-asserted-by":"crossref","unstructured":"Liu C, He J (2017) Access control to web pages based on user browsing behavior. In: 2017 IEEE 9th international conference on communication software and networks (ICCSN). IEEE, pp 1016\u20131020","DOI":"10.1109\/ICCSN.2017.8230264"},{"issue":"9","key":"2160_CR101","doi-asserted-by":"publisher","first-page":"2477","DOI":"10.1109\/TITS.2017.2649541","volume":"18","author":"H Liu","year":"2017","unstructured":"Liu H, Taniguchi T, Tanaka Y, Takenaka K, Bando T (2017) Visualization of driving behavior based on hidden feature extraction by using deep learning. IEEE Trans Intell Transp Syst 18(9):2477\u20132489","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"2160_CR102","unstructured":"Liu W, Yan H, Zhou W, Lei Z (2010) Network user dial-up behavior analysis. In: 2010 international conference on future information technology and management engineering (FITME), vol 1. IEEE, pp 39\u201343"},{"key":"2160_CR103","unstructured":"LLC G (2005) Google scholar. https:\/\/scholar.google.es\/, [Online: accessed 08-Sept-2020]"},{"issue":"3","key":"2160_CR104","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s12652-010-0043-x","volume":"3","author":"A Lotfi","year":"2012","unstructured":"Lotfi A, Langensiepen C, Mahmoud SM, Akhlaghinia MJ (2012) Smart homes for the elderly dementia sufferers: identification and prediction of abnormal behaviour. J Ambient Intell Human Comput 3 (3):205\u2013218","journal-title":"J Ambient Intell Human Comput"},{"key":"2160_CR105","unstructured":"Lu Z, Sagduyu Y (2016) Risk assessment based access control with text and behavior analysis for document management. In: Military communications conference, MILCOM 2016-2016 IEEE. IEEE, pp 37\u201342"},{"key":"2160_CR106","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1016\/j.future.2018.04.085","volume":"93","author":"X Luo","year":"2019","unstructured":"Luo X, Jiang C, Wang W, Xu Y, Wang JH, Zhao W (2019) User behavior prediction in social networks using weighted extreme learning machine with distribution optimization. Futur Gener Comput Syst 93:1023\u20131035","journal-title":"Futur Gener Comput Syst"},{"key":"2160_CR107","first-page":"2579","volume":"9","author":"M Lvd","year":"2008","unstructured":"Lvd M, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9:2579\u20132605","journal-title":"J Mach Learn Res"},{"key":"2160_CR108","doi-asserted-by":"crossref","unstructured":"Mahbub U, Chellappa R (2016) PATH: person authentication using trace histories. In: Ubiquitous computing, electronics & mobile communication conference (UEMCON), IEEE Annual. IEEE, pp 1\u20138","DOI":"10.1109\/UEMCON.2016.7777911"},{"key":"2160_CR109","doi-asserted-by":"crossref","unstructured":"Manca M, Parvin P, Patern\u00f2 F, Santoro C (2017) Detecting anomalous elderly behaviour in ambient assisted living. In: Proceedings of the ACM SIGCHI symposium on engineering interactive computing systems. ACM, pp 63\u201368","DOI":"10.1145\/3102113.3102128"},{"key":"2160_CR110","doi-asserted-by":"publisher","first-page":"12284","DOI":"10.1109\/ACCESS.2018.2795383","volume":"6","author":"J Mao","year":"2018","unstructured":"Mao J, Bian J, Bai G, Wang R, Chen Y, Xiao Y, Liang Z (2018) Detecting malicious behaviors in JavaScript applications. IEEE Access 6:12284\u201312294","journal-title":"IEEE Access"},{"key":"2160_CR111","doi-asserted-by":"crossref","unstructured":"Mirsky Y, Shapira B, Rokach L, Elovici Y (2015) pcstream: A stream clustering algorithm for dynamically detecting and managing temporal contexts. In: Pacific-Asia conference on knowledge discovery and data mining. Springer, pp 119\u2013133","DOI":"10.1007\/978-3-319-18032-8_10"},{"key":"2160_CR112","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.pmcj.2016.07.006","volume":"35","author":"Y Mirsky","year":"2017","unstructured":"Mirsky Y, Shabtai A, Shapira B, Elovici Y, Rokach L (2017) Anomaly detection for smartphone data streams. Perv Mob Comput 35:83\u2013107","journal-title":"Perv Mob Comput"},{"key":"2160_CR113","doi-asserted-by":"crossref","unstructured":"Misbahuddin M, Bindhumadhava B, Dheeptha B (2017) Design of a risk based authentication system using machine learning techniques. In: 2017 IEEE Smartworld, ubiquitous intelligence & computing, advanced & trusted computed, scalable computing & communications, cloud & big data computing, internet of people and smart city innovation. IEEE, pp 1\u20136","DOI":"10.1109\/UIC-ATC.2017.8397628"},{"issue":"2","key":"2160_CR114","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1109\/JPROC.2006.888405","volume":"95","author":"C Miyajima","year":"2007","unstructured":"Miyajima C, Nishiwaki Y, Ozawa K, Wakita T, Itou K, Takeda K, Itakura F (2007) Driver modeling based on driving behavior and its evaluation in driver identification. Proc IEEE 95 (2):427\u2013437","journal-title":"Proc IEEE"},{"issue":"1","key":"2160_CR115","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1109\/JSYST.2013.2279732","volume":"8","author":"Y Mo","year":"2014","unstructured":"Mo Y, Chen J, Xie X, Luo C, Yang LT (2014) Cloud-based mobile multimedia recommendation system with user behavior information. IEEE Syst J 8(1):184\u2013193","journal-title":"IEEE Syst J"},{"key":"2160_CR116","doi-asserted-by":"crossref","unstructured":"Moghaddam S, Helmy A (2011) Multidimensional modeling and analysis of wireless users online activity and mobility: A neural-networks map approach. In: Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems. ACM, pp 401\u2013408","DOI":"10.1145\/2068897.2068965"},{"key":"2160_CR117","doi-asserted-by":"crossref","unstructured":"Molloy I, Dickens L, Morisset C, Cheng PC, Lobo J, Russo A (2012) Risk-based security decisions under uncertainty. In: Proceedings of the second ACM conference on data and application security and privacy. ACM, pp 157\u2013168","DOI":"10.1145\/2133601.2133622"},{"issue":"6","key":"2160_CR118","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/79.543975","volume":"13","author":"TK Moon","year":"1996","unstructured":"Moon TK (1996) The expectation-maximization algorithm. IEEE Sig Process Mag 13(6):47\u201360","journal-title":"IEEE Sig Process Mag"},{"key":"2160_CR119","first-page":"797","volume":"93","author":"MM Moya","year":"1993","unstructured":"Moya MM, Koch MW, Hostetler LD (1993) One-class classifier networks for target recognition applications. NASA STI\/Recon Technical Report 93:797\u2013801","journal-title":"NASA STI\/Recon Technical Report"},{"issue":"4","key":"2160_CR120","first-page":"339","volume":"8","author":"A Muallem","year":"2017","unstructured":"Muallem A, Shetty S, Pan JW, Zhao J, Biswal B (2017) Hoeffding tree algorithms for anomaly detection in streaming datasets: a survey. J Inf Secur 8(4):339\u2013361","journal-title":"J Inf Secur"},{"key":"2160_CR121","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.procs.2015.03.073","volume":"45","author":"M Narvekar","year":"2015","unstructured":"Narvekar M, Banu SS (2015) Predicting user\u2019s web navigation behavior using hybrid approach. Procedia Comput Sci 45:3\u201312","journal-title":"Procedia Comput Sci"},{"issue":"4","key":"2160_CR122","doi-asserted-by":"publisher","first-page":"049901","DOI":"10.1117\/1.2819119","volume":"16","author":"NM Nasrabadi","year":"2007","unstructured":"Nasrabadi NM (2007) Pattern recognition and machine learning. J Elec Imag 16(4):049901","journal-title":"J Elec Imag"},{"key":"2160_CR123","doi-asserted-by":"publisher","DOI":"10.1201\/9780429505546","volume-title":"A first course in fuzzy logic","author":"HT Nguyen","year":"2018","unstructured":"Nguyen HT, Walker CL, Walker EA (2018) A first course in fuzzy logic. CRC Press, Boca Raton"},{"issue":"3","key":"2160_CR124","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1109\/JBHI.2015.2478903","volume":"20","author":"Y Nishiyama","year":"2016","unstructured":"Nishiyama Y, Okoshi T, Yonezawa T, Nakazawa J, Takashio K, Tokuda H (2016) Toward health exercise behavior change for teams using lifelog sharing models. IEEE J Biomed Health Inf 20 (3):775\u2013786","journal-title":"IEEE J Biomed Health Inf"},{"key":"2160_CR125","doi-asserted-by":"crossref","unstructured":"Ojt\u00e1\u0161 P, Pe\u0161ka L (2014) e-Shop user preferences via user behavior. In: 2014 11th international conference on e-Business (ICE-B). IEEE, pp 68\u201375","DOI":"10.5220\/0005102300680075"},{"issue":"4","key":"2160_CR126","doi-asserted-by":"crossref","first-page":"e3188","DOI":"10.1002\/ett.3188","volume":"29","author":"J Pacheco","year":"2018","unstructured":"Pacheco J, Hariri S (2018) Anomaly behavior analysis for IoT sensors. Trans Emerg Telecommun Technol 29(4):e3188","journal-title":"Trans Emerg Telecommun Technol"},{"key":"2160_CR127","first-page":"1","volume":"50","author":"Y Pan","year":"2019","unstructured":"Pan Y, He F, Yu H, Li H (2019) Learning adaptive trust strength with user roles of truster and trustee for trust-aware recommender systems. Appl Intell 50:1\u201314","journal-title":"Appl Intell"},{"key":"2160_CR128","doi-asserted-by":"crossref","unstructured":"Pantic M, Pentland A, Nijholt A, Huang TS (2007) Human computing and machine understanding of human behavior: a survey. In: Artifical intelligence for human computing. Springer, pp 47\u201371","DOI":"10.1007\/978-3-540-72348-6_3"},{"issue":"11","key":"2160_CR129","doi-asserted-by":"publisher","first-page":"10059","DOI":"10.1016\/j.eswa.2012.02.038","volume":"39","author":"DH Park","year":"2012","unstructured":"Park DH, Kim HK, Choi IY, Kim JK (2012) A literature review and classification of recommender systems research. Expert Syst Appl 39(11):10059\u201310072","journal-title":"Expert Syst Appl"},{"issue":"4","key":"2160_CR130","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1109\/MSP.2016.2555335","volume":"33","author":"VM Patel","year":"2016","unstructured":"Patel VM, Chellappa R, Chandra D, Barbello B (2016) Continuous user authentication on mobile devices: Recent progress and remaining challenges. IEEE Signal Proc Mag 33(4):49\u201361","journal-title":"IEEE Signal Proc Mag"},{"key":"2160_CR131","doi-asserted-by":"crossref","unstructured":"Perozzi B, Al-Rfou R, Skiena S (2014) Deepwalk: Online learning of social representations. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 701\u2013710","DOI":"10.1145\/2623330.2623732"},{"issue":"4","key":"2160_CR132","doi-asserted-by":"publisher","first-page":"1322","DOI":"10.1109\/JSYST.2014.2350019","volume":"9","author":"T Qin","year":"2015","unstructured":"Qin T, Guan X, Wang C, Liu Z (2015) MUCM: Multilevel user cluster mining based on behavior profiles for network monitoring. IEEE Syst J 9(4):1322\u20131333","journal-title":"IEEE Syst J"},{"key":"2160_CR133","doi-asserted-by":"crossref","unstructured":"Qiu F, Cho J (2006) Automatic identification of user interest for personalized search. In: Proceedings of the 15th international conference on World Wide Web. ACM, pp 727\u2013736","DOI":"10.1145\/1135777.1135883"},{"key":"2160_CR134","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-019-01493-6","volume":"49","author":"M Raeiszadeh","year":"2019","unstructured":"Raeiszadeh M, Tahayori H, Visconti A (2019) Discovering varying patterns of normal and interleaved adls in smart homes. Appl Intell 49:1\u201314","journal-title":"Appl Intell"},{"issue":"2","key":"2160_CR135","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1016\/j.dss.2010.11.006","volume":"50","author":"P Ravisankar","year":"2011","unstructured":"Ravisankar P, Ravi V, Rao GR, Bose I (2011) Detection of financial statement fraud and feature selection using data mining techniques. Decision Support Sys 50(2):491\u2013500","journal-title":"Decision Support Sys"},{"key":"2160_CR136","doi-asserted-by":"publisher","first-page":"987","DOI":"10.1016\/j.procs.2010.12.162","volume":"3","author":"S Raza","year":"2011","unstructured":"Raza S, Haider S (2011) Suspicious activity reporting using dynamic bayesian networks. Procedia Comput Sci 3:987\u2013991","journal-title":"Procedia Comput Sci"},{"key":"2160_CR137","unstructured":"Riva O, Qin C, Strauss K, Lymberopoulos D (2012) Progressive authentication: deciding when to authenticate on mobile phones. In: USENIX security symposium, microsoft research, pp 301\u2013316"},{"key":"2160_CR138","first-page":"301","volume":"143","author":"B Ro\u017eac","year":"2012","unstructured":"Ro\u017eac B, Sernec R, Ko\u0161ir A, Kos A (2012) User behavior analysis based on identity management systems\u2019 log data. Mach Learn 143:301","journal-title":"Mach Learn"},{"key":"2160_CR139","doi-asserted-by":"crossref","unstructured":"Ryu S, Kang YJ, Lee H (2018) A study on detection of anomaly behavior in automation industry. In: 2018 20th international conference on advanced communication technology (ICACT). IEEE, pp 377\u2013380","DOI":"10.23919\/ICACT.2018.8323763"},{"key":"2160_CR140","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-018-01402-3","volume":"49","author":"AK Sahu","year":"2019","unstructured":"Sahu AK, Dwivedi P (2019) User profile as a bridge in cross-domain recommender systems for sparsity reduction. Appl Intell 49:1\u201321","journal-title":"Appl Intell"},{"issue":"1","key":"2160_CR141","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/TDSC.2016.2536605","volume":"15","author":"A Saracino","year":"2018","unstructured":"Saracino A, Sgandurra D, Dini G, Martinelli F (2018) Madam: Effective and efficient behavior-based android malware detection and prevention. IEEE Trans Depend Sec Comput 15(1):83\u201397","journal-title":"IEEE Trans Depend Sec Comput"},{"key":"2160_CR142","doi-asserted-by":"crossref","unstructured":"Sarker IH, Colman A, Kabir MA, Han J (2016) Behavior-oriented time segmentation for mining individualized rules of mobile phone users. In: 2016 IEEE international conference on data science and advanced analytics (DSAA). IEEE, pp 488\u2013497","DOI":"10.1109\/DSAA.2016.60"},{"key":"2160_CR143","unstructured":"Science S (2004) Springer. https:\/\/link.springer.com\/, [Online: accessed 08-Sept-2020]"},{"issue":"4","key":"2160_CR144","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1109\/TITS.2007.903441","volume":"8","author":"S Sekizawa","year":"2007","unstructured":"Sekizawa S, Inagaki S, Suzuki T, Hayakawa S, Tsuchida N, Tsuda T, Fujinami H (2007) Modeling and recognition of driving behavior based on stochastic switched ARX model. IEEE Trans Intell Transport Sys 8(4):593\u2013606","journal-title":"IEEE Trans Intell Transport Sys"},{"key":"2160_CR145","doi-asserted-by":"crossref","unstructured":"Shashanka M, Shen MY, Wang J (2016) User and entity behavior analytics for enterprise security. In: 2016 IEEE international conference on big data (big data). IEEE, pp 1867\u2013 1874","DOI":"10.1109\/BigData.2016.7840805"},{"issue":"1","key":"2160_CR146","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/TIFS.2017.2737969","volume":"13","author":"C Shen","year":"2018","unstructured":"Shen C, Li Y, Chen Y, Guan X, Maxion RA (2018) Performance analysis of multi-motion sensor behavior for active smartphone authentication. IEEE Trans Inf Forensics Sec 13(1):48\u201362","journal-title":"IEEE Trans Inf Forensics Sec"},{"issue":"12","key":"2160_CR147","doi-asserted-by":"publisher","first-page":"1502","DOI":"10.1109\/TSMC.2015.2417837","volume":"45","author":"B Shi","year":"2015","unstructured":"Shi B, Xu L, Hu J, Tang Y, Jiang H, Meng W, Liu H (2015) Evaluating driving styles by normalizing driving behavior based on personalized driver modeling. IEEE Trans Sys Man Cybern Sys 45(12):1502\u20131508","journal-title":"IEEE Trans Sys Man Cybern Sys"},{"key":"2160_CR148","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-019-01477-6","volume":"49","author":"H Shi","year":"2019","unstructured":"Shi H, Chen L, Xu Z, Lyu D (2019) Personalized location recommendation using mobile phone usage information. Appl Intell 49:1\u201314","journal-title":"Appl Intell"},{"issue":"5","key":"2160_CR149","doi-asserted-by":"publisher","first-page":"376","DOI":"10.21276\/ijircst.2017.5.5.3","volume":"5","author":"G Shrivastava","year":"2017","unstructured":"Shrivastava G, Shrivastava S (2017) Analysis of customer behavior in online retail marketplace using Hadoop. Int J Innov Res Comput Sci Technol 5(5):376\u2013380","journal-title":"Int J Innov Res Comput Sci Technol"},{"key":"2160_CR150","doi-asserted-by":"crossref","unstructured":"Shumway RH, Stoffer DS (2017) ARIMA models. In: Time series analysis and its applications. Springer, pp 75\u2013163","DOI":"10.1007\/978-3-319-52452-8_3"},{"key":"2160_CR151","volume-title":"Tactics of scientific research","author":"M Sidman","year":"1960","unstructured":"Sidman M (1960) Tactics of scientific research. Basic Books, Incorporated, Pub, New York"},{"key":"2160_CR152","doi-asserted-by":"crossref","unstructured":"S\u0131lahtaro\u011flu G, D\u00f6nerta\u015fli H (2015) Analysis and prediction of E-customers\u2019 behavior by mining clickstream data. In: 2015 IEEE International Conference on Big data (big data). IEEE, pp 1466\u20131472","DOI":"10.1109\/BigData.2015.7363908"},{"key":"2160_CR153","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.jnca.2018.03.030","volume":"112","author":"K Singh","year":"2018","unstructured":"Singh K, Singh P, Kumar K (2018) User behavior analytics-based classification of application layer HTTP-GET flood attacks. J Netw Comput Appl 112:97\u2013114","journal-title":"J Netw Comput Appl"},{"key":"2160_CR154","first-page":"92904","volume-title":"Science and human behavior","author":"BF Skinner","year":"1953","unstructured":"Skinner BF (1953) Science and human behavior. Simon and Schuster, New York, p 92904"},{"key":"2160_CR155","doi-asserted-by":"crossref","unstructured":"Slaninov\u00e1 K (2013) User behavioural patterns and reduced user profiles extracted from log files. In: 2013 13th international conference on intelligent systems design and applications (ISDA). IEEE, pp 289\u2013294","DOI":"10.1109\/ISDA.2013.6920751"},{"issue":"1","key":"2160_CR156","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s00521-018-3633-8","volume":"31","author":"A Somasundaram","year":"2019","unstructured":"Somasundaram A, Reddy S (2019) Parallel and incremental credit card fraud detection model to handle concept drift and data imbalance. Neural Comput Applic 31(1):3\u201314","journal-title":"Neural Comput Applic"},{"key":"2160_CR157","doi-asserted-by":"crossref","unstructured":"Soviany S, Pu\u015fcoci S (2015) An optimized classification method for human behavioral patterns recognition. In: E-Health and bioengineering conference (EHB), 2015. IEEE, pp 1\u20134","DOI":"10.1109\/EHB.2015.7391588"},{"issue":"3","key":"2160_CR158","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1109\/TITS.2006.874716","volume":"7","author":"D Srinivasan","year":"2006","unstructured":"Srinivasan D, Choy MC, Cheu RL (2006) Neural networks for real-time traffic signal control. IEEE Trans Intell Transport Sys 7(3):261\u2013272","journal-title":"IEEE Trans Intell Transport Sys"},{"issue":"1","key":"2160_CR159","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1016\/j.asoc.2012.08.028","volume":"13","author":"D Stevanovic","year":"2013","unstructured":"Stevanovic D, Vlajic N, An A (2013) Detection of malicious and non-malicious website visitors using unsupervised neural network learning. Appl Soft Comput 13(1):698\u2013708","journal-title":"Appl Soft Comput"},{"issue":"3","key":"2160_CR160","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1016\/j.cryobiol.2006.08.002","volume":"53","author":"KB Storey","year":"2006","unstructured":"Storey KB et al (2006) Evidence for a reduced transcriptional state during hibernation in ground squirrels. Cryobiology 53(3):310\u2013318","journal-title":"Cryobiology"},{"issue":"6","key":"2160_CR161","doi-asserted-by":"publisher","first-page":"1965","DOI":"10.1109\/JSEN.2011.2182341","volume":"12","author":"NK Suryadevara","year":"2012","unstructured":"Suryadevara NK, Mukhopadhyay SC (2012) Wireless sensor network based home monitoring system for wellness determination of elderly. IEEE Sensors J 12(6):1965\u20131972","journal-title":"IEEE Sensors J"},{"key":"2160_CR162","doi-asserted-by":"crossref","unstructured":"Tai CS, Hong JH, Fu LC (2019) A real-time demand-side management system considering user behavior using deep q-learning in home area network. In: 2019 IEEE international conference on systems, man and cybernetics (SMC). IEEE, pp 4050\u20134055","DOI":"10.1109\/SMC.2019.8914266"},{"key":"2160_CR163","doi-asserted-by":"crossref","unstructured":"Tang B, Hu Q, Lin D (2017) Reducing false positives of user-to-entity first-access alerts for user behavior analytics. In: 2017 IEEE International conference on data mining workshops (ICDMW). IEEE, pp 804\u2013811","DOI":"10.1109\/ICDMW.2017.111"},{"key":"2160_CR164","doi-asserted-by":"crossref","unstructured":"Tapia EM, Intille SS, Larson K (2004) Activity recognition in the home using simple and ubiquitous sensors. In: International conference on pervasive computing. Springer, pp 158\u2013175","DOI":"10.1007\/978-3-540-24646-6_10"},{"key":"2160_CR165","doi-asserted-by":"crossref","unstructured":"Tax DM, Duin RP (1998) Outlier detection using classifier instability. In: Joint IAPR international workshops on statistical techniques in pattern recognition (SPR) and structural and syntactic pattern recognition (SSPR). Springer, pp 593\u2013601","DOI":"10.1007\/BFb0033283"},{"key":"2160_CR166","unstructured":"The Association for Computing Machinery (1947) acm. https:\/\/dl.acm.org\/, [Online: accessed 08-Sept-2020]"},{"key":"2160_CR167","doi-asserted-by":"crossref","unstructured":"Tseng VS, Chou CH, Yang KQ, Tseng JC (2017) A big data analytical framework for sports behavior mining and personalized health services. In: 2017 Conference on technologies and applications of artificial intelligence (TAAI). IEEE, pp 178\u2013183","DOI":"10.1109\/TAAI.2017.47"},{"key":"2160_CR168","doi-asserted-by":"crossref","unstructured":"Udantha M, Ranathunga S, Dias G (2016) Modelling website user behaviors by combining the EM and DBSCAN algorithms. In: Moratuwa engineering research conference (MERCon), 2016. IEEE, pp 168\u2013173","DOI":"10.1109\/MERCon.2016.7480134"},{"issue":"5","key":"2160_CR169","doi-asserted-by":"publisher","first-page":"2437","DOI":"10.1109\/TSG.2016.2548565","volume":"7","author":"Y Wang","year":"2016","unstructured":"Wang Y, Chen Q, Kang C, Xia Q (2016) Clustering of electricity consumption behavior dynamics toward big data applications. IEEE Trans Smart Grid 7(5):2437\u20132447","journal-title":"IEEE Trans Smart Grid"},{"key":"2160_CR170","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1016\/j.future.2014.02.015","volume":"37","author":"Z Wang","year":"2014","unstructured":"Wang Z, Tu L, Guo Z, Yang LT, Huang B (2014) Analysis of user behaviors by mining large network data sets. Futur Gener Comput Syst 37:429\u2013437","journal-title":"Futur Gener Comput Syst"},{"issue":"2","key":"2160_CR171","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MSP.2008.28","volume":"6","author":"JL Wayman","year":"2008","unstructured":"Wayman JL (2008) Biometrics in identity management systems. IEEE Sec Priv 6(2):30\u201337","journal-title":"IEEE Sec Priv"},{"issue":"4","key":"2160_CR172","doi-asserted-by":"publisher","first-page":"1302","DOI":"10.1016\/j.jnca.2011.03.004","volume":"34","author":"M Xie","year":"2011","unstructured":"Xie M, Han S, Tian B, Parvin S (2011) Anomaly detection in wireless sensor networks: a survey. J Netw Comput Appl 34(4):1302\u20131325","journal-title":"J Netw Comput Appl"},{"key":"2160_CR173","doi-asserted-by":"crossref","unstructured":"Xie Y, Phoha VV (2001) Web user clustering from access log using belief function. In: Proceedings of the 1st international conference on knowledge capture. ACM, pp 202\u2013208","DOI":"10.1145\/500737.500768"},{"key":"2160_CR174","doi-asserted-by":"crossref","unstructured":"Xing K, Zhang B, Zhou B, Liu Y (2011) Behavior based user interests extraction algorithm. In: Internet of things (ithings\/CPSCom), 2011 international conference on and 4th international conference on cyber, physical and social computing. IEEE, pp 448\u2013452","DOI":"10.1109\/iThings\/CPSCom.2011.70"},{"key":"2160_CR175","doi-asserted-by":"crossref","unstructured":"Xu G, Zhang Y, Yi X (2008) Modelling user behaviour for web recommendation using lda model. In: Web intelligence and intelligent agent technology, 2008. WI-IAT\u201908. IEEE\/WIC\/ACM international conference on, IEEE, vol 3, pp 529\u2013532","DOI":"10.1109\/WIIAT.2008.313"},{"key":"2160_CR176","unstructured":"Xu J, Liu H (2010) Web user clustering analysis based on KMeans algorithm. In: 2010 International conference on information, networking and automation (ICINA). IEEE, pp V2\u20136"},{"issue":"1","key":"2160_CR177","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1109\/TETC.2014.2381512","volume":"3","author":"J Yang","year":"2014","unstructured":"Yang J, Qiao Y, Zhang X, He H, Liu F, Cheng G (2014) Characterizing user behavior in mobile internet. IEEE Trans Emerg Topics in Computing 3(1):95\u2013106","journal-title":"IEEE Trans Emerg Topics in Computing"},{"key":"2160_CR178","doi-asserted-by":"crossref","unstructured":"Yang W, Zhang L, He Z, Zhuang L (2012) Optimized two-stage fuzzy control for urban traffic signals at isolated intersection and Paramics simulation. In: 2012 15th international IEEE conference on intelligent transportation systems. IEEE, pp 391\u2013396","DOI":"10.1109\/ITSC.2012.6338691"},{"issue":"3","key":"2160_CR179","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1016\/j.dss.2010.03.001","volume":"49","author":"YC Yang","year":"2010","unstructured":"Yang YC (2010) Web user behavioral profiling for user identification. Decis Support Syst 49 (3):261\u2013271","journal-title":"Decis Support Syst"},{"key":"2160_CR180","doi-asserted-by":"crossref","unstructured":"Yinan D, Hao Y, Zhenming L (2009) Broadband dial-up user behavior identification and analysis. In: 2nd IEEE international conference on broadband network & multimedia technology, 2009. IC-BNMT\u201909. IEEE, pp 316\u2013322","DOI":"10.1109\/ICBNMT.2009.5348502"},{"key":"2160_CR181","doi-asserted-by":"crossref","unstructured":"Zaman M, Siddiqui T, Amin MR, Hossain MS (2015) Malware detection in Android by network traffic analysis. In: 2015 International on networking systems and security (NSyss), pp 1\u20135. IEEE","DOI":"10.1109\/NSysS.2015.7043530"},{"key":"2160_CR182","doi-asserted-by":"crossref","unstructured":"Zechel P, Streiter R, Bogenberger K, Goehner U (2019) Probabilistic interaction-aware occupancy prediction for vehicles in arbitrary road scenes. In: 2019 Third IEEE international conference on robotic computing (IRC). IEEE, pp 423\u2013424","DOI":"10.1109\/IRC.2019.00081"},{"issue":"2","key":"2160_CR183","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.1109\/TIE.2018.2815949","volume":"66","author":"S Zhai","year":"2019","unstructured":"Zhai S, Wang Z, Yan X, He G (2019) Appliance flexibility analysis considering user behavior in home energy management system using smart plugs. IEEE Trans Ind Electron 66(2):1391\u20131401","journal-title":"IEEE Trans Ind Electron"},{"key":"2160_CR184","doi-asserted-by":"crossref","unstructured":"Zhang W, Fan Q (2010) Identification of abnormal driving state based on driver\u2019s model 2010 International on control automation and systems (ICCAS). IEEE, pp 14\u201318","DOI":"10.1109\/ICCAS.2010.5669943"},{"key":"2160_CR185","unstructured":"Zhang X, Han Y, Xu W, Wang Q (2019) Hoba: A novel feature engineering methodology for credit card fraud detection with a deep learning architecture. Inf Sci"},{"issue":"4","key":"2160_CR186","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1109\/MIS.2017.3121551","volume":"32","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Yang R, Zhang K, Jiang H, Zhang JJ (2017) Consumption behavior analytics-aided energy forecasting and dispatch. IEEE Intell Syst 32(4):59\u201363","journal-title":"IEEE Intell Syst"},{"key":"2160_CR187","doi-asserted-by":"crossref","unstructured":"Zhao P, Yan C, Jiang C (2016) Authenticating web user\u2019s identity through browsing sequences modeling. In: 2016 IEEE 16th international conference on data mining workshops (ICDMW). IEEE, pp 335\u2013342","DOI":"10.1109\/ICDMW.2016.0054"},{"key":"2160_CR188","doi-asserted-by":"crossref","unstructured":"Zhou G, Mou N, Fan Y, Pi Q, Bian W, Zhou C, Zhu X, Gai K (2019) Deep interest evolution network for click-through rate prediction. In: Proceedings of the AAAI conference on artificial intelligence, vol 33, pp 5941\u20135948","DOI":"10.1609\/aaai.v33i01.33015941"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-02160-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-020-02160-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-02160-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T06:55:55Z","timestamp":1697698555000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-020-02160-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,26]]},"references-count":188,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["2160"],"URL":"https:\/\/doi.org\/10.1007\/s10489-020-02160-x","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,26]]},"assertion":[{"value":"16 December 2020","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 January 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}