{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T13:15:20Z","timestamp":1726060520905},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811518980"},{"type":"electronic","value":"9789811518997"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-981-15-1899-7_8","type":"book-chapter","created":{"date-parts":[[2019,11,27]],"date-time":"2019-11-27T21:02:38Z","timestamp":1574888558000},"page":"107-119","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Distributed Big Data Discretization Algorithm Under Spark"],"prefix":"10.1007","author":[{"given":"Yeung","family":"Chan","sequence":"first","affiliation":[]},{"given":"Xia Jie","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jing Hua","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,11,28]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2015.12.006","volume":"98","author":"S Garc\u00eda","year":"2016","unstructured":"Garc\u00eda, S., Luengo, J., Herrera, F.: Tutorial on practical tips of the most influential data preprocessing algorithms in data mining. Knowl.-Based Syst. 98, 1\u201329 (2016)","journal-title":"Knowl.-Based Syst."},{"issue":"1","key":"8_CR2","first-page":"5","volume":"6","author":"S Ram\u00edrez-Gallego","year":"2016","unstructured":"Ram\u00edrez-Gallego, S., Garc\u00eda, S., Mouri\u00f1o-Tal\u00edn, H., et al.: Data discretization: taxonomy and big data challenge. Wiley Interdisc. Rev.: Data Min. Knowl. Discovery 6(1), 5\u201321 (2016)","journal-title":"Wiley Interdisc. Rev.: Data Min. Knowl. Discovery"},{"issue":"3","key":"8_CR3","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1214\/aos\/1176343842","volume":"5","author":"R Beran","year":"1977","unstructured":"Beran, R.: Minimum hellinger distance estimates for parametric models. Ann. Stat. 5(3), 445\u2013463 (1977)","journal-title":"Ann. Stat."},{"issue":"1","key":"8_CR4","first-page":"5","volume":"6","author":"S Ram\u00edrez-Gallego","year":"2016","unstructured":"Ram\u00edrez-Gallego, S., et al.: Data discretization: taxonomy and big data challenge. Wiley Interdiscip. Rev.: Data Min. Knowl. Discov. 6(1), 5\u201321 (2016)","journal-title":"Wiley Interdiscip. Rev.: Data Min. Knowl. Discov."},{"issue":"3","key":"8_CR5","first-page":"235","volume":"16","author":"SL Salzberg","year":"1994","unstructured":"Salzberg, S.L.: C4.5: programs for machine learning by J. Ross Quinlan. Morgan Kaufmann Publishers, Inc. 1993. Mach. Learn. 16(3), 235\u2013240 (1994)","journal-title":"Mach. Learn."},{"key":"8_CR6","doi-asserted-by":"crossref","unstructured":"Au, W.H., Chan, K.C., Wong, A.K.C.: A fuzzy approach to partitioning continuous attributes for classification. IEEE Educational Activities Department (2006)","DOI":"10.1109\/TKDE.2006.70"},{"issue":"05","key":"8_CR7","first-page":"103","volume":"55","author":"Y Liu","year":"2018","unstructured":"Liu, Y.: Parallel discrete data preparation optimization in data mining. J. Sichuan Univ. (Nat. Sci. Ed.) 55(05), 103\u2013109 (2018)","journal-title":"J. Sichuan Univ. (Nat. Sci. Ed.)"},{"issue":"4","key":"8_CR8","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1016\/j.knosys.2006.06.005","volume":"20","author":"CH Lee","year":"2007","unstructured":"Lee, C.H.: A Hellinger-based discretization method for numeric attributes in classification learning. Knowl.-Based Syst. 20(4), 419\u2013425 (2007)","journal-title":"Knowl.-Based Syst."},{"key":"8_CR9","unstructured":"Wu, C., Guo, S., Li, C.: Research on discretization algorithm based on gaussian mixture model. Small Microcomput. Syst. (4), 21 (2018)"},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Ram\u00edrez-Gallego, S., Garc\u00eda, S., Mouri\u00f1o-Tal\u00edn, H., et al.: Distributed entropy minimization discretizer for big data analysis under apache spark. In: 2015 IEEE Trustcom\/BigDataSE\/ISPA, vol. 2, pp. 33\u201340. IEEE (2015)","DOI":"10.1109\/Trustcom.2015.559"},{"key":"8_CR11","unstructured":"Wang, L.: Power big data attribute discretization method based on cloud computing technology. Digit. Technol. Appl. (1), 56\u201358 (2015)"},{"issue":"11","key":"8_CR12","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1145\/2934664","volume":"59","author":"M Zaharia","year":"2016","unstructured":"Zaharia, M., Xin, R.S., Wendell, P., et al.: Apache spark: a unified engine for big data processing. Commun. ACM 59(11), 56\u201365 (2016)","journal-title":"Commun. ACM"},{"key":"8_CR13","first-page":"2","volume":"17","author":"J Alcal\u00e1-Fdez","year":"2011","unstructured":"Alcal\u00e1-Fdez, J., Fern\u00e1ndez, A., Luengo, J., et al.: Keel data-mining software tool: data set repository, integration of algorithms and experimental analysis framework. J. Multiple-Valued Logic Soft Comput. 17, 2\u20133 (2011)","journal-title":"J. Multiple-Valued Logic Soft Comput."},{"key":"8_CR14","unstructured":"UCI Machine Learning Repository: Heterogeneity Activity Recognition data. \nhttp:\/\/archive.ics.uci.edu\/ml\/datasets\/Heterogeneity+Activity+Recognition"}],"container-title":["Communications in Computer and Information Science","Big Data"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-1899-7_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,27]],"date-time":"2019-11-27T21:05:54Z","timestamp":1574888754000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-1899-7_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9789811518980","9789811518997"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-1899-7_8","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"28 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BigData","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF Conference on Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Wuhan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"26 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bigdat2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/grid.hust.edu.cn\/bigdata2019","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"324","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"9% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}