{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T08:02:02Z","timestamp":1771920122043,"version":"3.50.1"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2018,9,6]],"date-time":"2018-09-06T00:00:00Z","timestamp":1536192000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2019,3]]},"DOI":"10.1007\/s10586-018-2848-x","type":"journal-article","created":{"date-parts":[[2018,9,6]],"date-time":"2018-09-06T15:36:38Z","timestamp":1536248198000},"page":"241-270","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["A fog based load forecasting strategy for smart grids using big electrical data"],"prefix":"10.1007","volume":"22","author":[{"given":"Asmaa H.","family":"Rabie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shereen H.","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hesham A.","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed I.","family":"Saleh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,6]]},"reference":[{"issue":"4","key":"2848_CR1","doi-asserted-by":"publisher","first-page":"956","DOI":"10.1007\/s11036-017-0961-3","volume":"23","author":"M Ozger","year":"2017","unstructured":"Ozger, M., Cetinkaya, O., Akan, O.B.: Energy harvesting cognitive radio networking for IoT-enabled smart grid. Mob. Netw. Appl. 23(4), 956\u2013966 (2017)","journal-title":"Mob. Netw. Appl."},{"key":"2848_CR2","unstructured":"Saleem, Y., Crespi, N., Rehmani, M.H., Copeland, R.: Internet of things-aided smart grid: technologies, architectures, applications, prototypes, and future research directions (2017). arXiv:1704.08977"},{"key":"2848_CR3","volume-title":"Fog Computing in the Internet of Things, ISBN 978-3-319-57638-1, ISBN 978-3-319-57639-8 (eBook)","author":"AM Rahmani","year":"2018","unstructured":"Rahmani, A.M., Liljeberg, P., Preden, J., Jantsch, A.: Fog Computing in the Internet of Things, ISBN 978-3-319-57638-1, ISBN 978-3-319-57639-8 (eBook). Springer, New York (2018)"},{"issue":"8","key":"2848_CR4","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/MC.2016.245","volume":"49","author":"AV Dastjerdi","year":"2016","unstructured":"Dastjerdi, A.V., Buyya, R.: Fog computing: helping the internet of things realize its potential. Computer 49(8), 112\u2013116 (2016)","journal-title":"Computer"},{"issue":"5","key":"2848_CR5","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1109\/MC.2016.145","volume":"49","author":"W Shi","year":"2016","unstructured":"Shi, W., Dustdar, S.: The promise of edge computing. Computer 49(5), 78\u201381 (2016)","journal-title":"Computer"},{"key":"2848_CR6","unstructured":"Mahmud, R., Buyya, R.: Fog computing: a taxonomy, survey and future directions (2016). arXiv:1611.05539"},{"key":"2848_CR7","unstructured":"Gangurde, H.D.: Feature selection using clustering approach for big data, Int. J. Comput. Appl. (0975\u20138887) Innovations and Trends in Computer and Communication Engineering (ITCCE), pp. 1\u20133 (2014)"},{"issue":"5","key":"2848_CR8","first-page":"2319","volume":"4","author":"L Revathi","year":"2015","unstructured":"Revathi, L., Appandiraj, A.: Hadoop based parallel framework for feature subset selection in big data. Int. J. Innov. Res. Sci. 4(5), 2319\u20138753 (2015)","journal-title":"Int. J. Innov. Res. Sci."},{"issue":"3","key":"2848_CR9","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1016\/j.aei.2015.06.001","volume":"29","author":"N Sajadfara","year":"2015","unstructured":"Sajadfara, N., Mab, Y.: A hybrid cost estimation framework based on feature-oriented data mining approach. Adv. Eng. Inform. 29(3), 633\u2013647 (2015)","journal-title":"Adv. Eng. Inform."},{"issue":"2","key":"2848_CR10","first-page":"7","volume":"1","author":"R Kumar","year":"2012","unstructured":"Kumar, R., Verma, R.: Classification algorithms for data mining: a survey. Int. J. Innov. Eng. Technol. (IJIET) 1(2), 7\u201314 (2012)","journal-title":"Int. J. Innov. Eng. Technol. (IJIET)"},{"key":"2848_CR11","unstructured":"Aziz, A.S.A., Azar, A.T., Salama, M.A.: Genetic algorithm with different feature selection techniques for anomaly detectors generation. In: Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, pp. 769\u2013774 (2013)"},{"key":"2848_CR12","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.eswa.2017.05.002","volume":"84","author":"LM Abualigah","year":"2017","unstructured":"Abualigah, L.M., Khader, A.T., Al-Beta, M.A., Alomari, O.A.: Text feature selection with a robust weight scheme and dynamic dimension reduction to text document clustering. Expert Syst. Appl. 84, 24\u201336 (2017)","journal-title":"Expert Syst. Appl."},{"issue":"9","key":"2848_CR13","doi-asserted-by":"publisher","first-page":"2795","DOI":"10.1007\/s00521-016-2204-0","volume":"28","author":"L Zhang","year":"2017","unstructured":"Zhang, L., Shan, L., Wang, J.: Optimal feature selection using distance-based discrete firefly algorithm with mutual information criterion. Neural Comput. Appl. 28(9), 2795\u20132808 (2017)","journal-title":"Neural Comput. Appl."},{"key":"2848_CR14","doi-asserted-by":"publisher","first-page":"1165","DOI":"10.1111\/tgis.12268","volume":"21","author":"D Chutia","year":"2017","unstructured":"Chutia, D., Bhattacharyya, D.K., Sarma, J., Raju, P.N.L.: An effective ensemble classification framework using random forests and a correlation based feature selection technique. Trans. GIS 21, 1165\u20131178 (2017)","journal-title":"Trans. GIS"},{"key":"2848_CR15","doi-asserted-by":"crossref","unstructured":"Ortega, L., Han, Z.H.: Complexity theory and language development: In: Celebration of diane Larsen-freeman, John Benjamins B.V., Amsterdam, ICCN 2017028813 (2017)","DOI":"10.1075\/lllt.48"},{"key":"2848_CR16","first-page":"2017","volume":"1\u201333","author":"A Mardani","year":"2017","unstructured":"Mardani, A., Nilashi, M., Antucheviciene, J., Tavana, M., Bausys, R., Ibrahim, O.: Recent fuzzy generalisations of rough sets theory: a systematic review and methodological critique of the literature. Complexity 1\u201333, 2017 (2017)","journal-title":"Complexity"},{"issue":"6","key":"2848_CR17","doi-asserted-by":"publisher","first-page":"1580","DOI":"10.1109\/TSP.2016.2645515","volume":"65","author":"M Rahmani","year":"2017","unstructured":"Rahmani, M., Atia, G.K.: Randomized robust subspace recovery and outlier detection for high dimensional data matrices. IEEE Trans. Signal Process. 65(6), 1580\u20131594 (2017)","journal-title":"IEEE Trans. Signal Process."},{"key":"2848_CR18","doi-asserted-by":"crossref","unstructured":"Wang, Y., Ke, W., Tao X.: A feature selection method for large-scale network traffic classification based on spark. www.mdpi.com\/journal\/information , 7(1) (2016)","DOI":"10.3390\/info7010006"},{"key":"2848_CR19","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/978-3-319-27000-5_6","volume":"5","author":"W Bouaguel","year":"2016","unstructured":"Bouaguel, W.: A new approach for wrapper feature selection using genetic algorithm for big data. Part of the Proceedings in Adaptation, Learning and Optimization book series, Intelligent and Evolutionary Systems, Springer 5, 75\u201383 (2016)","journal-title":"Part of the Proceedings in Adaptation, Learning and Optimization book series, Intelligent and Evolutionary Systems, Springer"},{"issue":"2","key":"2848_CR20","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.ipl.2015.07.005","volume":"116","author":"SY Jiang","year":"2016","unstructured":"Jiang, S.Y., Wang, L.X.: Efficient feature selection based on correlation measure between continuous and discrete features. Inf. Process. Lett. 116(2), 203\u2013215 (2016)","journal-title":"Inf. Process. Lett."},{"issue":"3","key":"2848_CR21","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1007\/s10844-011-0172-5","volume":"38","author":"P Shamsinejadbabki","year":"2012","unstructured":"Shamsinejadbabki, P., Saraee, M.: A new unsupervised feature selection method for text clustering based on genetic algorithms. J. Intell. Inf. Syst. 38(3), 669\u2013684 (2012)","journal-title":"J. Intell. Inf. Syst."},{"issue":"1","key":"2848_CR22","doi-asserted-by":"publisher","first-page":"119","DOI":"10.14257\/ijhit.2016.9.1.11","volume":"9","author":"H Wang","year":"2016","unstructured":"Wang, H., Liu, S.: An effective feature selection approach using the hybrid filter wrapper. Int. J. Hybrid Inf. Technol. 9(1), 119\u2013128 (2016)","journal-title":"Int. J. Hybrid Inf. Technol."},{"key":"2848_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2047-2501-1-10","volume":"1","author":"J Xie","year":"2013","unstructured":"Xie, J., Lei, J., Xie, W., Shi, Y., Liu, X.: Two-stage hybrid feature selection algorithms for diagnosing erythemato-squamous diseases. Health Inf. Sci. Syst. 1, 1\u201310 (2013)","journal-title":"Health Inf. Sci. Syst."},{"key":"2848_CR24","doi-asserted-by":"crossref","unstructured":"Wang, W., Gombault, S.: Efficient detection of DDoS attacks with important attributes. In: Proceedings of the Risks and Security of Internet and Systems on CRiSIS\u201908 Third International Conference, IEEE, pp. 61\u201367 (2008)","DOI":"10.1109\/CRISIS.2008.4757464"},{"issue":"1","key":"2848_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TKDE.2011.181","volume":"25","author":"Q Song","year":"2013","unstructured":"Song, Q., Ni, J., Wang, G.: Fast clustering-based feature subset selection algorithm for high dimensional data. IEEE Trans. Knowl. Data Eng. 25(1), 1\u201314 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"2848_CR26","doi-asserted-by":"crossref","unstructured":"Wang, K., Xu, C., Guo S.: Big data analytics for price forecasting in smart grids. In: Proceedings of the Global Communications Conference (GLOBECOM), IEEE (2016)","DOI":"10.1109\/GLOCOM.2016.7841630"},{"issue":"10","key":"2848_CR27","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/MCOM.2017.1700168","volume":"55","author":"L Li","year":"2017","unstructured":"Li, L., Ota, K., Dong, M.: When weather matters: IoT-based electrical load forecasting for smart grid. IEEE Commun. Mag. 55(10), 46\u201351 (2017)","journal-title":"IEEE Commun. Mag."},{"key":"2848_CR28","doi-asserted-by":"crossref","unstructured":"Okay, F.Y., Ozdemir, S.: A fog computing based smart grid model. International Symposium on Networks, Computers and Communications (ISNCC), Yasmine Hammamet, pp. 1\u20136 (2016)","DOI":"10.1109\/ISNCC.2016.7746062"},{"key":"2848_CR29","doi-asserted-by":"crossref","unstructured":"Shahryari, K., Oghaddam, A.A.: Demand side management using the internet of energy based on fog and cloud computing. In: Proceedings of the 10th IEEE International Conference on Internet of Things (iThings 2017), pp. 1\u20136 (2017)","DOI":"10.1109\/iThings-GreenCom-CPSCom-SmartData.2017.143"},{"key":"2848_CR30","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1016\/j.procs.2015.07.250","volume":"6","author":"M Jaradat","year":"2015","unstructured":"Jaradat, M., Jarrah, M., Bousselham, A., Jararweh, Y., Al-Ayyouba, M.: The internet of energy: smart sensor networks and big data management for smart grid. Procedia Comput. Sci. 6, 592\u2013597 (2015)","journal-title":"Procedia Comput. Sci."},{"issue":"2","key":"2848_CR31","first-page":"738","volume":"8","author":"CN Yu","year":"2017","unstructured":"Yu, C.N., Mirowski, P., Ho, T.K.: A sparse coding approach to household electricity demand forecasting in smart grids. IEEE Trans. Smart Grid 8(2), 738\u2013748 (2017)","journal-title":"IEEE Trans. Smart Grid"},{"issue":"2","key":"2848_CR32","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/j.aei.2010.10.002","volume":"25","author":"A Ahmeda","year":"2011","unstructured":"Ahmeda, A., Korresb, N.E., Ploennigsc, J., Elhadid, H., Menzela, K.: Mining building performance data for energy-efficient operation. Adv. Eng. Inform. 25(2), 341\u2013354 (2011)","journal-title":"Adv. Eng. Inform."},{"key":"2848_CR33","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/B978-0-12-805321-8.00002-1","volume-title":"The power grid","author":"AA Edris","year":"2017","unstructured":"Edris, A.A., D\u2019Andrade, B.W.: Transmission grid smart technologies. The power grid, pp. 37\u201355. Elsevier, New York (2017)"},{"key":"2848_CR34","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.apenergy.2016.12.058","volume":"194","author":"I Dincer","year":"2017","unstructured":"Dincer, I., Acar, C.: Smart energy systems for a sustainable future. Appl. Energy 194, 225\u2013235 (2017)","journal-title":"Appl. Energy"},{"key":"2848_CR35","unstructured":"Jestes, J.: efficient summarization techniques for massive data. A thesis submitted to the faculty of the University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy, School of Computing, The University of Utah, (2013)"},{"issue":"3","key":"2848_CR36","doi-asserted-by":"publisher","first-page":"2165","DOI":"10.3233\/JIFS-162006","volume":"32","author":"KA Vidhya","year":"2017","unstructured":"Vidhya, K.A., Geetha, T.V.: Rough set theory for document clustering: a review. J. Intell. Fuzzy Syst. 32(3), 2165\u20132185 (2017)","journal-title":"J. Intell. Fuzzy Syst."},{"issue":"3","key":"2848_CR37","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1007\/s00500-016-2385-6","volume":"22","author":"S Gu","year":"2018","unstructured":"Gu, S., Cheng, R., Jin, Y.: Feature selection for high-dimensional classification using a competitive swarm optimizer. Soft Comput. 22(3), 811\u2013822 (2018)","journal-title":"Soft Comput."},{"key":"2848_CR38","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1007\/978-981-10-4762-6_48","volume-title":"Advances in systems, control and automation, part of the lecture notes in electrical engineering book series","author":"S Venkataraman","year":"2017","unstructured":"Venkataraman, S., Selvaraj, R.: Optimal and novel hybrid feature selection framework for effective data classification. Advances in systems, control and automation, part of the lecture notes in electrical engineering book series, vol. 442, pp. 499\u2013514. Springer, Singapore (2017)"},{"key":"2848_CR39","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.neucom.2016.11.047","volume":"226","author":"C Pascoal","year":"2017","unstructured":"Pascoal, C., Oliveira, M.R., Pacheco, A., Valadas, R.: Theoretical evaluation of feature selection methods based on mutual information. Neurocomputing 226, 168\u2013181 (2017)","journal-title":"Neurocomputing"},{"issue":"1","key":"2848_CR40","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1080\/09720502.2016.1259769","volume":"20","author":"YH Li","year":"2017","unstructured":"Li, Y.H.: Text feature selection algorithm based on Chi square rank correlation factorization. J. Interdiscip. Math. 20(1), 153\u2013160 (2017)","journal-title":"J. Interdiscip. Math."},{"key":"2848_CR41","first-page":"2017","volume":"1\u201310","author":"KD Rajab","year":"2017","unstructured":"Rajab, K.D.: New hybrid features selection method: a case study on websites phishing. Secur Commun Netw 1\u201310, 2017 (2017)","journal-title":"Secur Commun Netw"},{"key":"2848_CR42","first-page":"443","volume-title":"Information systems design and intelligent applications","author":"HP Vinutha","year":"2018","unstructured":"Vinutha, H.P., Poornima, B.: An ensemble classifier approach on different feature selection methods for intrusion detection. Information systems design and intelligent applications, pp. 443\u2013451. Springer, New York (2018)"},{"key":"2848_CR43","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1007\/978-3-319-33410-3_20","volume-title":"Modelling and implementation of complex systems","author":"H Djellali","year":"2016","unstructured":"Djellali, H., Zine, N.G., Azizi, N.: Two stages feature selection based on filter ranking methods and SVMRFE on medical applications. Modelling and implementation of complex systems, pp. 281\u2013293. Springer, New York (2016)"},{"key":"2848_CR44","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.knosys.2014.12.002","volume":"75","author":"AI Saleh","year":"2015","unstructured":"Saleh, A.I., El Desouky, A.I., Ali, S.H.: Promoting the performance of vertical recommendation systems by applying new classification techniques. Knowl Based Syst. 75, 192\u2013223 (2015)","journal-title":"Knowl Based Syst."},{"issue":"1","key":"2848_CR45","first-page":"25","volume":"20","author":"OU Rebrovs","year":"2017","unstructured":"Rebrovs, O.U., Ku\u013ce\u0161ova, G.: Comparative analysis of fuzzy set defuzzification methods in the context of ecological risk assessment. Inf. Technol. Manag. Sci. 20(1), 25\u201329 (2017)","journal-title":"Inf. Technol. Manag. Sci."},{"key":"2848_CR46","volume-title":"Expert systems: principles and programming","author":"J Giarratano","year":"2004","unstructured":"Giarratano, J., Riley, G.: Expert systems: principles and programming, 4th edn. Course Technology Inc, Boston (2004)","edition":"4"},{"issue":"3","key":"2848_CR47","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s12205-018-1337-3","volume":"22","author":"X Feng","year":"2018","unstructured":"Feng, X., Li, S., Yuan, C., Zeng, P., Sun, Y.: Prediction of slope stability using naive Bayes classifier. KSCE J. Civ. Eng. 22(3), 941\u2013950 (2018)","journal-title":"KSCE J. Civ. Eng."},{"key":"2848_CR48","unstructured":"European Network on Intelligent TEchnologies for Smart Adaptive Systems. http:\/\/www.eunite.org\/ . The competition page is: http:\/\/neuron.tuke.sk\/competition\/"},{"key":"2848_CR49","doi-asserted-by":"crossref","unstructured":"Zdravevski, E., Lameski, P., Kulakov, A., Jakimovski, B., Filiposka, S., Trajanov, D.: Feature ranking based on information gain for large classification problems with MapReduce. Trustcom\/BigDataSE\/ISPA, IEEE (2015)","DOI":"10.1109\/Trustcom.2015.580"},{"issue":"4","key":"2848_CR50","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1080\/03772063.2015.1021385","volume":"61","author":"C Jin","year":"2015","unstructured":"Jin, C., Ma, T., Hou, R.: Chi square statistics feature selection based on term frequency and distribution for text categorization. IETE J. Res. 61(4), 351\u2013362 (2015)","journal-title":"IETE J. Res."},{"key":"2848_CR51","doi-asserted-by":"crossref","unstructured":"Alyam, R., Alhajja, J., Alnajran, B., Elaalam, I., Alqahtan, A., Aldhaffer, N., Owolab, T.O., Olatun, S.O.: Investigating the effect of correlation based feature selection on breast cancer diagnosis using artificial neural network and support vector machines. In: Proceedings of the International Conference on Informatics, Health & Technology (ICIHT), IEEE (2017)","DOI":"10.1109\/ICIHT.2017.7899011"},{"key":"2848_CR52","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2017.2723563","author":"K Wang","year":"2017","unstructured":"Wang, K., Xu, C., Zhang, Y., Guo, S., Zomaya, A.Y.: Robust big data analytics for electricity price forecasting in the smart grid. IEEE Trans Big Data (2017). https:\/\/doi.org\/10.1109\/TBDATA.2017.2723563","journal-title":"IEEE Trans Big Data"},{"issue":"25","key":"2848_CR53","doi-asserted-by":"publisher","first-page":"163","DOI":"10.3906\/elk-1501-98","volume":"2017","author":"NB Nazar","year":"2017","unstructured":"Nazar, N.B., Senthilkumar, R.: An online approach for feature selection for classification in big data. Turk. J. Electr. Eng. Comput. Sci. 2017(25), 163\u2013171 (2017)","journal-title":"Turk. J. Electr. Eng. Comput. Sci."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10586-018-2848-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-018-2848-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-018-2848-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,6]],"date-time":"2025-07-06T22:59:24Z","timestamp":1751842764000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10586-018-2848-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,6]]},"references-count":53,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,3]]}},"alternative-id":["2848"],"URL":"https:\/\/doi.org\/10.1007\/s10586-018-2848-x","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,6]]},"assertion":[{"value":"15 March 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 August 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 September 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}