{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T03:44:19Z","timestamp":1775274259114,"version":"3.50.1"},"publisher-location":"Cham","reference-count":55,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030043025","type":"print"},{"value":"9783030043032","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-04303-2_5","type":"book-chapter","created":{"date-parts":[[2018,11,16]],"date-time":"2018-11-16T05:42:01Z","timestamp":1542346921000},"page":"63-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation"],"prefix":"10.1007","author":[{"given":"Ole J.","family":"Mengshoel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Priya K.","family":"Sundararajan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik","family":"Reed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongzhen","family":"Piao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Briana","family":"Johnson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,17]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","DOI":"10.1201\/9780203913673","volume-title":"Power System State Estimation: Theory and Implementation","author":"A Abur","year":"2004","unstructured":"Abur, A., Exposito, A.G.: Power System State Estimation: Theory and Implementation, vol. 24. CRC Press, Boca Raton (2004)"},{"key":"5_CR2","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1016\/j.ijepes.2014.04.046","volume":"62","author":"M Aien","year":"2014","unstructured":"Aien, M., Rashidinejad, M., Kouhi, S., Fotuhi-Firuzabad, M., Najafi Ravadanegh, S.: Real time probabilistic power system state estimation. Int. J. Electr. Power Energy Syst. 62, 383\u2013390 (2014)","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"5_CR3","unstructured":"Andersen, S.K., Olesen, K.G., Jensen, F.V., Jensen, F.: HUGIN\u2013a shell for building Bayesian belief universes for expert systems. In: Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI 1989), Detroit, MI, pp. 1080\u20131085 (1989)"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Basak, A., Brinster, I., Ma, X., Mengshoel, O.J.: Accelerating Bayesian network parameter learning using Hadoop and MapReduce. In: Proceedings of the BigMine 2012, Beijing, China (2012)","DOI":"10.1145\/2351316.2351330"},{"key":"5_CR5","unstructured":"Bills, G.W.: On-line stability analysis study. Technical report RP 901\u20131. Electric Power Research Institute (1970)"},{"issue":"3","key":"5_CR6","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1109\/TPAS.1974.293973","volume":"PAS\u201393","author":"B Borkowska","year":"1974","unstructured":"Borkowska, B.: Probabilistic load flow. IEEE Trans. Power Appar. Syst. PAS\u201393(3), 752\u2013759 (1974)","journal-title":"IEEE Trans. Power Appar. Syst."},{"key":"5_CR7","unstructured":"Chavira, M., Darwiche, A.: Compiling Bayesian networks using variable elimination. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI 2007), Hyderabad, India, pp. 2443\u20132449 (2007)"},{"key":"5_CR8","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1109\/TPWRD.2002.1022804","volume":"17","author":"CF Chien","year":"2002","unstructured":"Chien, C.F., Chen, S.L., Lin, Y.S.: Using Bayesian network for fault location on distribution feeder. IEEE Trans. Power Deliv. 17, 785\u2013793 (2002)","journal-title":"IEEE Trans. Power Deliv."},{"key":"5_CR9","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/0004-3702(90)90060-D","volume":"42","author":"FG Cooper","year":"1990","unstructured":"Cooper, F.G.: The computational complexity of probabilistic inference using Bayesian belief networks. Artif. Intell. 42, 393\u2013405 (1990)","journal-title":"Artif. Intell."},{"issue":"1\u20132","key":"5_CR10","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/S0004-3702(00)00069-2","volume":"126","author":"A Darwiche","year":"2001","unstructured":"Darwiche, A.: Recursive conditioning. Artif. Intell. 126(1\u20132), 5\u201341 (2001)","journal-title":"Artif. Intell."},{"issue":"3","key":"5_CR11","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1145\/765568.765570","volume":"50","author":"A Darwiche","year":"2003","unstructured":"Darwiche, A.: A differential approach to inference in Bayesian networks. J. ACM 50(3), 280\u2013305 (2003)","journal-title":"J. ACM"},{"key":"5_CR12","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511811357","volume-title":"Modeling and Reasoning with Bayesian Networks","author":"A Darwiche","year":"2009","unstructured":"Darwiche, A.: Modeling and Reasoning with Bayesian Networks. Cambridge University Press, Cambridge (2009)"},{"key":"5_CR13","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/BF01890546","volume":"2","author":"AP Dawid","year":"1992","unstructured":"Dawid, A.P.: Applications of a general propagation algorithm for probabilistic expert systems. Stat. Comput. 2, 25\u201336 (1992)","journal-title":"Stat. Comput."},{"issue":"1\u20132","key":"5_CR14","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/S0004-3702(99)00059-4","volume":"113","author":"R Dechter","year":"1999","unstructured":"Dechter, R.: Bucket elimination: a unifying framework for reasoning. Artif. Intell. 113(1\u20132), 41\u201385 (1999)","journal-title":"Artif. Intell."},{"issue":"6","key":"5_CR15","doi-asserted-by":"publisher","first-page":"2253","DOI":"10.1109\/TPEL.2007.909252","volume":"22","author":"D Divan","year":"2007","unstructured":"Divan, D., Johal, H.: Distributed FACTS - a new concept for realizing grid power flow control. IEEE Trans. Power Electr. 22(6), 2253\u20132260 (2007)","journal-title":"IEEE Trans. Power Electr."},{"issue":"3","key":"5_CR16","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1023\/A:1022623210503","volume":"20","author":"D Heckerman","year":"1995","unstructured":"Heckerman, D., Geiger, D., Chickering, D.: Learning Bayesian networks: the combination of knowledge and statistical data. Mach. Learn. 20(3), 197\u2013243 (1995)","journal-title":"Mach. Learn."},{"key":"5_CR17","unstructured":"Holmstr\u00f6m, K.: TOMLAB - an environment for solving optimization problems in MATLAB. In: Proceedings of the Nordic MATLAB Conference, Stockholm, Sweden (1997)"},{"key":"5_CR18","doi-asserted-by":"crossref","unstructured":"Hu, Y., Kuh, A., Kavcic, A., Nakafuji, D.: Real-time state estimation on micro-grids. In: Proceedings of the 2011 International Joint Conference on Neural Networks, San Jose, CA, pp. 1378\u20131385 (2011)","DOI":"10.1109\/IJCNN.2011.6033385"},{"issue":"3","key":"5_CR19","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1109\/MCI.2011.941589","volume":"6","author":"Y Hu","year":"2011","unstructured":"Hu, Y., Kuh, A., Yang, T., Kavcic, A.: A belief propagation based power distribution system state estimator. IEEE Comput. Intell. Mag. 6(3), 36\u201346 (2011)","journal-title":"IEEE Comput. Intell. Mag."},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Hug, G.: Generation cost and system risk trade-off with corrective power flow control. In: Proceedings of the 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton, IL, pp. 1324\u20131331 (2012)","DOI":"10.1109\/Allerton.2012.6483371"},{"key":"5_CR21","unstructured":"Hutter, F., Hoos, H.H., St\u00fctzle, T.: Efficient stochastic local search for MPE solving. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI 2005), Edinburgh, Scotland, pp. 169\u2013174 (2005)"},{"key":"5_CR22","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1613\/jair.583","volume":"10","author":"TS Jaakkola","year":"1999","unstructured":"Jaakkola, T.S., Jordan, M.I.: Variational probabilistic inference and the QMR-DT database. J. Artif. Intell. Res. 10, 291\u2013322 (1999)","journal-title":"J. Artif. Intell. Res."},{"key":"5_CR23","first-page":"269","volume":"4","author":"FV Jensen","year":"1990","unstructured":"Jensen, F.V., Lauritzen, S.L., Olesen, K.G.: Bayesian updating in causal probabilistic networks by local computations. SIAM J. Comput. 4, 269\u2013282 (1990)","journal-title":"SIAM J. Comput."},{"key":"5_CR24","unstructured":"Kask, K., Dechter, R.: Stochastic local search for Bayesian networks. In: Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics (AISTATS 1999), Fort Lauderdale, FL (1999)"},{"key":"5_CR25","volume-title":"Probabilistic Graphical Methods: Principles and Techniques","author":"D Koller","year":"2009","unstructured":"Koller, D., Friedman, N.: Probabilistic Graphical Methods: Principles and Techniques. MIT Press, Cambridge (2009)"},{"issue":"2","key":"5_CR26","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1111\/j.2517-6161.1988.tb01721.x","volume":"50","author":"S Lauritzen","year":"1988","unstructured":"Lauritzen, S., Spiegelhalter, D.J.: Local computations with probabilities on graphical structures and their application to expert systems (with discussion). J. Roy. Stat. Soc. Ser. B 50(2), 157\u2013224 (1988)","journal-title":"J. Roy. Stat. Soc. Ser. B"},{"key":"5_CR27","unstructured":"Lerner, U., Parr, R., Koller, D., Biswas, G.: Bayesian fault detection and diagnosis in dynamic systems. In: Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI 2000), pp. 531\u2013537 (2000)"},{"key":"5_CR28","doi-asserted-by":"publisher","first-page":"984","DOI":"10.1016\/j.artint.2010.05.007","volume":"174","author":"OJ Mengshoel","year":"2010","unstructured":"Mengshoel, O.J.: Understanding the scalability of Bayesian network inference using clique tree growth curves. Artif. Intell. 174, 984\u20131006 (2010)","journal-title":"Artif. Intell."},{"issue":"5","key":"5_CR29","doi-asserted-by":"publisher","first-page":"874","DOI":"10.1109\/TSMCA.2010.2052037","volume":"40","author":"OJ Mengshoel","year":"2010","unstructured":"Mengshoel, O.J., Chavira, M., Cascio, K., Poll, S., Darwiche, A., Uckun, S.: Probabilistic model-based diagnosis: an electrical power system case study. IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum. 40(5), 874\u2013885 (2010)","journal-title":"IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum."},{"key":"5_CR30","unstructured":"Mengshoel, O.J., Darwiche, A., Uckun, S.: Sensor validation using Bayesian networks. In: Proceedings of the 9th International Symposium on Artificial Intelligence, Robotics, and Automation in Space (iSAIRAS 2008) (2008)"},{"issue":"16\u201317","key":"5_CR31","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1016\/j.artint.2006.09.003","volume":"170","author":"OJ Mengshoel","year":"2006","unstructured":"Mengshoel, O.J., Wilkins, D.C., Roth, D.: Controlled generation of hard and easy Bayesian networks: impact on maximal clique size in tree clustering. Artif. Intell. 170(16\u201317), 1137\u20131174 (2006)","journal-title":"Artif. Intell."},{"issue":"8","key":"5_CR32","doi-asserted-by":"publisher","first-page":"955","DOI":"10.1016\/j.artint.2007.09.010","volume":"172","author":"OJ Mengshoel","year":"2008","unstructured":"Mengshoel, O.J.: Understanding the role of noise in stochastic local search: analysis and experiments. Artif. Intell. 172(8), 955\u2013990 (2008)","journal-title":"Artif. Intell."},{"key":"5_CR33","doi-asserted-by":"crossref","unstructured":"Mohammadi, J., Hug, G., Kar, S.: A benders decomposition approach to corrective security constrained OPF with power flow control devices. In: Proceedings of the 2013 IEEE Power Energy Society General Meeting, pp. 1\u20135 (2013)","DOI":"10.1109\/PESMG.2013.6672684"},{"key":"5_CR34","doi-asserted-by":"crossref","unstructured":"Mohammadi, J., Hug, G., Kar, S.: Fully distributed DC-OPF approach for power flow control. In: 2015 IEEE Power Energy Society General Meeting, pp. 1\u20135 (2015)","DOI":"10.1109\/PESGM.2015.7285770"},{"key":"5_CR35","first-page":"2001","volume":"33","author":"KP Murphy","year":"2001","unstructured":"Murphy, K.P.: The Bayes net toolbox for MATLAB. Comput. Sci. Stat. 33, 2001 (2001)","journal-title":"Comput. Sci. Stat."},{"key":"5_CR36","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1613\/jair.1236","volume":"21","author":"JD Park","year":"2004","unstructured":"Park, J.D., Darwiche, A.: Complexity results and approximation strategies for MAP explanations. JAIR 21, 101\u2013133 (2004)","journal-title":"JAIR"},{"key":"5_CR37","volume-title":"Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference","author":"J Pearl","year":"1988","unstructured":"Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo (1988)"},{"key":"5_CR38","unstructured":"Poll, S., et al.: Advanced diagnostics and prognostics testbed. In: Proceedings of the 18th International Workshop on Principles of Diagnosis (DX-07), Nashville, TN, pp. 178\u2013185 (2007)"},{"issue":"5","key":"5_CR39","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1016\/j.ijar.2014.02.005","volume":"55","author":"B Ricks","year":"2014","unstructured":"Ricks, B., Mengshoel, O.J.: Diagnosis for uncertain, dynamic and hybrid domains using Bayesian networks and arithmetic circuits. Int. J. Approx. Reason. 55(5), 1207\u20131234 (2014)","journal-title":"Int. J. Approx. Reason."},{"key":"5_CR40","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/0004-3702(94)00092-1","volume":"82","author":"D Roth","year":"1996","unstructured":"Roth, D.: On the hardness of approximate reasoning. Artif. Intell. 82, 273\u2013302 (1996)","journal-title":"Artif. Intell."},{"key":"5_CR41","unstructured":"Saluja, A., Sundararajan, P., Mengshoel, O.J.: Age-layered expectation maximization for parameter learning in Bayesian networks. In: Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012), La Palma, Spain, pp. 424\u2013435 (2012)"},{"key":"5_CR42","doi-asserted-by":"crossref","unstructured":"Schenato, L., Barchi, G., Macii, D., Arghandeh, R., Poolla, K., Von Meier, A.: Bayesian linear state estimation using smart meters and PMUs measurements in distribution grids. In: Proceedings of the 2014 IEEE International Conference on Smart Grid Communications, pp. 572\u2013577 (2014)","DOI":"10.1109\/SmartGridComm.2014.7007708"},{"issue":"4","key":"5_CR43","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1007\/s11334-013-0214-y","volume":"9","author":"J Schumann","year":"2013","unstructured":"Schumann, J., et al.: Software health management with Bayesian networks. Innov. Syst. Softw. Eng. 9(4), 271\u2013292 (2013)","journal-title":"Innov. Syst. Softw. Eng."},{"issue":"1","key":"5_CR44","first-page":"1","volume":"6","author":"J Schumann","year":"2015","unstructured":"Schumann, J., Rozier, K.Y., Reinbacher, T., Mengshoel, O.J., Mbaya, T., Ippolito, C.: Towards real-time, on-board, hardware-supported sensor and software health management for unmanned aerial systems. Int. J. Progn. Health Manag. 6(1), 1\u201327 (2015)","journal-title":"Int. J. Progn. Health Manag."},{"issue":"3","key":"5_CR45","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1016\/0888-613X(89)90009-1","volume":"5","author":"PP Shenoy","year":"1989","unstructured":"Shenoy, P.P.: A valuation-based language for expert systems. Int. J. Approx. Reason. 5(3), 383\u2013411 (1989)","journal-title":"Int. J. Approx. Reason."},{"key":"5_CR46","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/0004-3702(94)90072-8","volume":"68","author":"E Shimony","year":"1994","unstructured":"Shimony, E.: Finding MAPs for belief networks is NP-hard. Artif. Intell. 68, 399\u2013410 (1994)","journal-title":"Artif. Intell."},{"key":"5_CR47","unstructured":"Soliman, W.M., Bahaa El Din, H.S., Wahab, M.A., Mansour, M.: Bayesian networks for fault diagnosis of large power generating stations. In: Proceedings of the 14th International Middle East Power Systems Conference, Cairo, Egypt, pp. 454\u2013459 (2005)"},{"key":"5_CR48","unstructured":"Sundararajan, P.K., Mengshoel, O.J.: A genetic algorithm for learning parameters in Bayesian networks using expectation maximization. In: Proceedings of the Eighth International Conference on Probabilistic Graphical Models (PGM 2016), Lugano, Switzerland, pp. 511\u2013522 (2016)"},{"issue":"99","key":"5_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TSG.2017.2749369","volume":"PP","author":"Y Weng","year":"2018","unstructured":"Weng, Y., Negi, R., Ilic, M.D.: Probabilistic joint state estimation for operational planning. IEEE Trans. Smart Grid PP(99), 1 (2018)","journal-title":"IEEE Trans. Smart Grid"},{"key":"5_CR50","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1109\/TPWRD.2005.858774","volume":"21","author":"Z Yongli","year":"2006","unstructured":"Yongli, Z., Limin, H., Jinling, L.: Bayesian network-based approach for power system fault diagnosis. IEEE Trans. Power Deliv. 21, 634\u2013639 (2006)","journal-title":"IEEE Trans. Power Deliv."},{"key":"5_CR51","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1613\/jair.305","volume":"5","author":"NL Zhang","year":"1996","unstructured":"Zhang, N.L., Poole, D.: Exploiting causal independence in Bayesian network inference. J. Artif. Intell. Res. 5, 301\u2013328 (1996)","journal-title":"J. Artif. Intell. Res."},{"key":"5_CR52","unstructured":"Zheng, L., Mengshoel, O.J.: Exploring multiple dimensions of parallelism in junction tree message passing. In: Proceedings of the 2013 UAI Application Workshops, pp. 87\u201396 (2013)"},{"key":"5_CR53","doi-asserted-by":"crossref","unstructured":"Zheng, L., Mengshoel, O.J.: Optimizing parallel belief propagation in junction trees using regression. In: Proceedings of 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2013), Chicago, IL (2013)","DOI":"10.1145\/2487575.2487611"},{"key":"5_CR54","unstructured":"Zheng, L., Mengshoel, O.J., Chong, J.: Belief propagation by message passing in junction trees: computing each message faster using GPU parallelization. In: Proceedings of the 27th Conference in Uncertainty in Artificial Intelligence (UAI 2011), Barcelona, Spain, pp. 822\u2013830 (2011)"},{"issue":"1","key":"5_CR55","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1109\/TPWRS.2010.2051168","volume":"26","author":"RD Zimmerman","year":"2011","unstructured":"Zimmerman, R.D., Murillo-S\u00e1nchez, C.E., Thomas, R.J.: MATPOWER: steady-state operations, planning, and analysis tools for power systems research and education. IEEE Trans. Power Syst. 26(1), 12\u201319 (2011)","journal-title":"IEEE Trans. Power Syst."}],"container-title":["Lecture Notes in Computer Science","Data Analytics for Renewable Energy Integration. Technologies, Systems and Society"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04303-2_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T02:45:15Z","timestamp":1775270715000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-04303-2_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030043025","9783030043032"],"references-count":55,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04303-2_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"DARE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Data Analytics for Renewable Energy Integration","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dublin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ireland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dare2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ecmlpkdd2018.org\/workshops\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}