{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T09:13:36Z","timestamp":1766049216174},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030295158"},{"type":"electronic","value":"9783030295165"}],"license":[{"start":{"date-parts":[[2019,8,24]],"date-time":"2019-08-24T00:00:00Z","timestamp":1566604800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-29516-5_31","type":"book-chapter","created":{"date-parts":[[2019,8,23]],"date-time":"2019-08-23T16:03:48Z","timestamp":1566576228000},"page":"391-401","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["High Quality Dataset for Machine Learning in the Business Intelligence Domain"],"prefix":"10.1007","author":[{"given":"Luisa","family":"Franchina","sequence":"first","affiliation":[]},{"given":"Federico","family":"Sergiani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,24]]},"reference":[{"key":"31_CR1","unstructured":"Cagala, T.: Improving Data Quality and Closing Data Gaps with Machine Learning. Deutsche Bundesbank, German Securities Holding Statistics (2017)"},{"issue":"1\u20132","key":"31_CR2","first-page":"1","volume":"10","author":"VN Gudivada","year":"2017","unstructured":"Gudivada, V.N., Apon, A., Dingh, J.: Data quality considerations for big data and machine learning: going beyond data cleaning and transformation. Int. J. Adv. Softw. 10(1\u20132), 1\u201320 (2017)","journal-title":"Int. J. Adv. Softw."},{"key":"31_CR3","doi-asserted-by":"crossref","unstructured":"Borovicka, T., Jirina Jr., M., Kordik, P., Jirina, M.: Selecting Representative Data Sets. Advances in Data Mining Knowledge Discovery and Application. Intech (2012)","DOI":"10.5772\/50787"},{"issue":"12","key":"31_CR4","doi-asserted-by":"publisher","first-page":"1781","DOI":"10.14778\/3229863.3229867","volume":"11","author":"Sebastian Schelter","year":"2018","unstructured":"Schelter, S., Lange, D., Schmidt, P., Celikel, M., Biessmann, F., Grafberger, A.: Automating large-scale data quality verification. In: VLDB Endowment Proceedings of the VLDB Endowment, vol. 11, no. 12, pp. 1781\u20131794. VLDB Endowment (2016)","journal-title":"Proceedings of the VLDB Endowment"},{"key":"31_CR5","unstructured":"Redman, T.C.: Bad Data Costs the U.S. 3 Trillion Per Year. Harvard Business Review (2016)"},{"key":"31_CR6","unstructured":"Echerson, W.W.: Data Quality and the Bottom Line, 1st edn. The Data Warehousing Institute (2002)"},{"issue":"1","key":"31_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3106235","volume":"9","author":"D Marcheggiani","year":"2017","unstructured":"Marcheggiani, D., Sebastiani, F.: On the effects of low-quality training data on information extraction from clinical reports. Data Inf. Qual. 9(1), 1\u201325 (2017)","journal-title":"Data Inf. Qual."},{"issue":"1","key":"31_CR8","first-page":"161","volume":"17","author":"N Zellal","year":"2017","unstructured":"Zellal, N., Zaouia, A.: An examination of factors influencing the quality of data in a data warehouse. IJCSNS Int. J. Comput. Sci. Netw. Secur. 17(1), 161\u2013169 (2017)","journal-title":"IJCSNS Int. J. Comput. Sci. Netw. Secur."},{"key":"31_CR9","volume-title":"Open Source Intelligence and Cyberspace","author":"A Teti","year":"2015","unstructured":"Teti, A.: Open Source Intelligence and Cyberspace, 1st edn. Rubbettino, Roma (2015)","edition":"1"},{"key":"31_CR10","first-page":"298","volume":"4","author":"L Collingwood","year":"2011","unstructured":"Collingwood, L., Wilkerson, J.: Tradeoffs in accuracy and efficiency in supervised learning methods. J. Inf. Technol. Polit. (JITP) 4, 298\u2013318 (2011)","journal-title":"J. Inf. Technol. Polit. (JITP)"},{"key":"31_CR11","unstructured":"Sessions, V., Valtorta, M.: The Effects of Data Quality on Machine Learning Algorithms. Research in Progress, University of South Carolina (2017)"},{"key":"31_CR12","unstructured":"Singh, H., Singh, P.B.: Business intelligence: effective machine learning for business administration. Int. J. IT Eng. Appl. Sci. Res. (IJIEASR) 2(1), 13\u201319 (2013)"},{"issue":"1","key":"31_CR13","first-page":"491","volume":"18","author":"Q Duy Vo","year":"2017","unstructured":"Duy Vo, Q., Jaya, T., Cho, S., De, P., Choi, B.J., Sael, L.: Next generation business intelligence and analytics: a survey. IEEE Commun. Surv. Tutor. 18(1), 491\u2013506 (2017)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"31_CR14","unstructured":"Financial Stability Board: Artificial Intelligence and Machine Learning in Financial Services. Financial Stability Board (2017)"},{"key":"31_CR15","unstructured":"Sapp, C.E.: Preparing and Architecting for Machine Learning. Gartner Technical Professional Advice (2017)"},{"issue":"13","key":"31_CR16","first-page":"28","volume":"165","author":"Z Pirani","year":"2017","unstructured":"Pirani, Z., Marewar, A., Bhavnagarwala, Z., Kamble, M.: Application of business intelligence using machine learning approach. Int. J. Comput. Appl. 165(13), 28\u201331 (2017)","journal-title":"Int. J. Comput. Appl."}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29516-5_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,23]],"date-time":"2019-08-23T16:13:50Z","timestamp":1566576830000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-29516-5_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,24]]},"ISBN":["9783030295158","9783030295165"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29516-5_31","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,8,24]]},"assertion":[{"value":"24 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Proceedings of SAI Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"London","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/IntelliSys","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}