{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:52:38Z","timestamp":1740099158119,"version":"3.37.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030017675"},{"type":"electronic","value":"9783030017682"}],"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\/978-3-030-01768-2_1","type":"book-chapter","created":{"date-parts":[[2018,10,4]],"date-time":"2018-10-04T16:48:08Z","timestamp":1538671688000},"page":"3-14","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Elements of an Automatic Data Scientist"],"prefix":"10.1007","author":[{"given":"Luc","family":"De Raedt","sequence":"first","affiliation":[]},{"given":"Hendrik","family":"Blockeel","sequence":"additional","affiliation":[]},{"given":"Samuel","family":"Kolb","sequence":"additional","affiliation":[]},{"given":"Stefano","family":"Teso","sequence":"additional","affiliation":[]},{"given":"Gust","family":"Verbruggen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,10,5]]},"reference":[{"key":"1_CR1","unstructured":"Bot.me: How artificial intelligence is pushing man and machine closer together. Technical Report, PwC (2017)"},{"issue":"6","key":"1_CR2","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1145\/2813885.2737952","volume":"50","author":"DW Barowy","year":"2015","unstructured":"Barowy, D.W., Gulwani, S., Hart, T., Zorn, B.: Flashrelate: extracting relational data from semi-structured spreadsheets using examples. SIGPLAN Not. 50(6), 218\u2013228 (2015)","journal-title":"SIGPLAN Not."},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Beldiceanu, N., Simonis, H.: A model seeker: extracting global constraint models from positive examples. In: Proceedings 18th International Conference on Principles and Practice of Constraint Programming. Lecture Notes in Computer Science, vol. 7514, pp. 141\u2013157 (2012)","DOI":"10.1007\/978-3-642-33558-7_13"},{"key":"1_CR4","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/j.artint.2015.08.001","volume":"244","author":"C Bessiere","year":"2017","unstructured":"Bessiere, C., Koriche, F., Lazaar, N., O\u2019Sullivan, B.: Constraint acquisition. Artif. Intell. 244, 315\u2013342 (2017)","journal-title":"Artif. Intell."},{"issue":"1\u20132","key":"1_CR5","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/S0004-3702(98)00034-4","volume":"101","author":"H Blockeel","year":"1998","unstructured":"Blockeel, H., De Raedt, L.: Top-down induction of first-order logical decision trees. Artif. Intell. 101(1\u20132), 285\u2013297 (1998)","journal-title":"Artif. Intell."},{"key":"1_CR6","unstructured":"Contreras-Ochando, L., Mart\u00ednez-Plumed, F., Ferri, C., Hern\u00e1ndez-Orallo, J., Ram\u00edrez-Quintana, M.J., Katayama, S.: Domain specific induction for data wrangling automation (demo). AutoML @ ICML 2017 (2017)"},{"key":"1_CR7","unstructured":"De Raedt, L., Kimmig, A., Toivonen, H.: Problog: a probabilistic prolog and its application in link discovery. In: Proceedings 20th International Joint Conference on Artificial Intelligence (2007)"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"De Raedt, L., Passerini, A., Teso, S.: Learning constraints from examples. In: Proceedings 32nd AAAI Conference on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.12217"},{"issue":"3","key":"1_CR9","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1017\/S1471068414000076","volume":"15","author":"D Fierens","year":"2015","unstructured":"Fierens, D., et al.: Inference and learning in probabilistic logic programs using weighted boolean formulas. Theory Pract. Log. Prog. 15(3), 358\u2013401 (2015)","journal-title":"Theory Pract. Log. Prog."},{"issue":"1","key":"1_CR10","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1145\/1925844.1926423","volume":"46","author":"Sumit Gulwani","year":"2011","unstructured":"Gulwani, S.: Automating string processing in spreadsheets using input-output examples. In: ACM SIGPLAN-SIGACT, POPL, pp. 317\u2013330 (2011)","journal-title":"ACM SIGPLAN Notices"},{"issue":"2","key":"1_CR11","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1145\/2076450.2076469","volume":"55","author":"HH Hoos","year":"2012","unstructured":"Hoos, H.H.: Programming by optimization. Commun. ACM 55(2), 70\u201380 (2012)","journal-title":"Commun. ACM"},{"key":"1_CR12","unstructured":"Hutter, F., Kotthoff, L., Vanschoren, J. (eds.): AutoML: methods, systems, challenges (2018). Draft available from: https:\/\/www.ml4aad.org\/book\/"},{"key":"1_CR13","unstructured":"Jin, Z., Cafarella, M., Jagadish, H., Kandel, S., Minar, M.: Unifacta: profiling-driven string pattern standardization. arXiv preprint arXiv:1803.00701 (2018)"},{"key":"1_CR14","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1038\/nature02236","volume":"427","author":"RD King","year":"2004","unstructured":"King, R.D., et al.: Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427, 247\u2013252 (2004)","journal-title":"Nature"},{"issue":"9\u201310","key":"1_CR15","doi-asserted-by":"publisher","first-page":"1441","DOI":"10.1007\/s10994-017-5640-x","volume":"106","author":"S Kolb","year":"2017","unstructured":"Kolb, S., Paramonov, S., Guns, T., De Raedt, L.: Learning constraints in spreadsheets and tabular data. Mach. Learn. 106(9\u201310), 1441\u20131468 (2017)","journal-title":"Mach. Learn."},{"key":"1_CR16","volume-title":"The Age of Intelligent Machines","author":"R Kurzweil","year":"1990","unstructured":"Kurzweil, R.: The Age of Intelligent Machines. MIT press, Cambridge (1990)"},{"key":"1_CR17","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.ijar.2017.10.029","volume":"93","author":"J Kwisthout","year":"2018","unstructured":"Kwisthout, J.: Approximate inference in bayesian networks: parameterized complexity results. Int. J. Approx. Reason. 93, 119\u2013131 (2018)","journal-title":"Int. J. Approx. Reason."},{"key":"1_CR18","volume-title":"Artificial Intelligence: A Modern Approach","author":"S Russell","year":"2010","unstructured":"Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn. Prentice Hall, Upper Saddle River (2010)","edition":"3"},{"issue":"1","key":"1_CR19","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/1471-2105-11-2","volume":"11","author":"Leander Schietgat","year":"2010","unstructured":"Schietgat, L., Vens, C., Struyf, J., Blockeel, H., Kocev, D., Dzeroski, S.: Predicting gene function using hierarchical multi-label decision tree ensembles. BMC Bioinform. 11(2) (2010)","journal-title":"BMC Bioinformatics"},{"issue":"3","key":"1_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2480741.2480748","volume":"45","author":"Floarea Serban","year":"2013","unstructured":"Serban, F., Vanschoren, J., Kietz, J.U., Bernstein, A.: A survey of intelligent assistants for data analysis. ACM Comput. Surv. (CSUR) 45(3) (2013)","journal-title":"ACM Computing Surveys"},{"issue":"1","key":"1_CR21","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1145\/2914770.2837668","volume":"51","author":"R Singh","year":"2016","unstructured":"Singh, R., Gulwani, S.: Transforming spreadsheet data types using examples. SIGPLAN Not. 51(1), 343\u2013356 (2016)","journal-title":"SIGPLAN Not."},{"key":"1_CR22","unstructured":"Steinruecken, C., Smith, E., Janz, D., Lloyd, J., Ghahramani, Z.: The automated statistician (2018). Draft available from: https:\/\/www.ml4aad.org\/book\/"},{"issue":"2","key":"1_CR23","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/s10994-008-5077-3","volume":"73","author":"C Vens","year":"2008","unstructured":"Vens, C., Struyf, J., Schietgat, L., Dzeroski, S., Blockeel, H.: Decision trees for hierarchical multi-label classification. Mach. Learn. 73(2), 185\u2013214 (2008)","journal-title":"Mach. Learn."},{"key":"1_CR24","unstructured":"Verbruggen, G., De Raedt, L.: Towards automated relational data wrangling. In: Proceedings of AutoML 2017@ ECML-PKDD: automatic selection, configuration and composition of machine learning algorithms, pp. 18\u201326 (2017)"},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Verbruggen, G., De Raedt, L.: Automatically wrangling spreadsheets into machine learning data formats. In: Duivesteijn, W., et al. (eds.) IDA 2018. LNCS, vol. 11191, pp. 367\u2013379. Springer, Cham (2018)","DOI":"10.1007\/978-3-030-01768-2_30"},{"key":"1_CR26","doi-asserted-by":"crossref","unstructured":"Wolputte, E.V., Korneva, E., Blockeel, H.: MERCS: multi-directional ensembles of regression and classification trees. In: Proceedings 32nd AAAI Conference on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.11735"}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis XVII"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01768-2_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,3]],"date-time":"2022-09-03T08:52:27Z","timestamp":1662195147000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-01768-2_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030017675","9783030017682"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01768-2_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"IDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligent Data Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"\u2018s-Hertogenbosch","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","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":"24 October 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 October 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ida2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ida2018.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}