{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:00:56Z","timestamp":1743109256178,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031514678"},{"type":"electronic","value":"9783031514685"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-51468-5_4","type":"book-chapter","created":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T09:02:58Z","timestamp":1705136578000},"page":"51-64","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["On Line Teaching Data Classification Method for Ramp Control Specialty in Universities Based on Machine Learning Model"],"prefix":"10.1007","author":[{"given":"Miao","family":"Guo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaxiu","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,14]]},"reference":[{"issue":"3","key":"4_CR1","first-page":"34","volume":"225","author":"H Wen","year":"2023","unstructured":"Wen, H., Guo, W., Li, X.: A novel deep clustering network using multi-representation autoencoder and adversarial learning for large cross-domain fault diagnosis of rolling bearings. Expert Syst. Appl. 225(3), 34\u201338 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"4_CR2","first-page":"312","volume":"65","author":"N Rezaei","year":"2023","unstructured":"Rezaei, N., Pezhmani, Y., Mohammadiani, R.P.: Optimal stochastic self-scheduling of a water-energy virtual power plant considering data clustering and multiple storage systems. J. Energy Storage 65(3), 312\u2013319 (2023)","journal-title":"J. Energy Storage"},{"issue":"1","key":"4_CR3","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1038\/s41598-023-33223-x","volume":"13","author":"D Soares","year":"2023","unstructured":"Soares, D., Henriques, R., Gromicho, M., et al.: Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis. Sci. Rep. 13(1), 89\u201396 (2023)","journal-title":"Sci. Rep."},{"key":"4_CR4","unstructured":"Pan, L., Xie, S., Cao, X.: Application of multi-classification algorithms based on ECOC in MOOC data mining. J. Jimei Univ. (Nat. Sci.) 26(2), 146\u2013151 (2021)"},{"issue":"3","key":"4_CR5","first-page":"543","volume":"42","author":"X Zhang","year":"2020","unstructured":"Zhang, X., An, J., Cao, R.: A data stream classification algorithm based on adaptive random forest ensemble model. Comput. Eng. Sci. 42(3), 543\u2013549 (2020)","journal-title":"Comput. Eng. Sci."},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Shyaa, M., Zainol, Z., Abdullah, R., et al.: Enhanced intrusion detection with data stream classification and concept drift guided by the incremental learning genetic programming combiner. Sensors (Basel, Switzerland) 23(7), 113\u2013119 (2023)","DOI":"10.3390\/s23073736"},{"issue":"3","key":"4_CR7","first-page":"1341","volume":"629","author":"H Ding","year":"2023","unstructured":"Ding, H., Sun, Y., Huang, N., et al.: RVGAN-TL: a generative adversarial networks and transfer learning-based hybrid approach for imbalanced data classification. Inf. Sci. 629(3), 1341\u20131348 (2023)","journal-title":"Inf. Sci."},{"issue":"2","key":"4_CR8","first-page":"131","volume":"82","author":"R Varatharajan","year":"2022","unstructured":"Varatharajan, R., Manogaran, G., Priyan, M.: Retraction note: a big data classification approach using LDA with an enhanced SVM method for ECG signals in cloud computing. Multimedia Tools Appl. 82(2), 131\u2013139 (2022)","journal-title":"Multimedia Tools Appl."},{"issue":"13","key":"4_CR9","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/s11227-022-04500-9","volume":"78","author":"P Prakash","year":"2022","unstructured":"Prakash, P., Senthil, R.: HSVNN: an efficient medical data classification using dimensionality reduction combined with hybrid support vector neural network. J. Supercomput. 78(13), 145\u2013152 (2022)","journal-title":"J. Supercomput."},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"LeonMedina, J., Par\u00e9s, N., Anaya, M., et al.: Pozo Francesc. Data classification methodology for electronic noses using uniform manifold approximation and projection and extreme learning machine. Mathematics 10(1), 77\u201382 (2021)","DOI":"10.3390\/math10010029"},{"issue":"2","key":"4_CR11","first-page":"34","volume":"15","author":"M Jacintha","year":"2021","unstructured":"Jacintha, M., Nagesh, P.: Hyperspectral image data classification with refined spectral spatial features based on stacked autoencoder approach. Recent Patents Eng. 15(2), 34\u201339 (2021)","journal-title":"Recent Patents Eng."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","e-Learning, e-Education, and Online Training"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-51468-5_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T09:08:44Z","timestamp":1705136924000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-51468-5_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031514678","9783031514685"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-51468-5_4","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"14 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"eLEOT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on E-Learning, E-Education, and Online Training","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Yantai","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eleot2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eleot.eai-conferences.org\/2023\/","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":"Confy +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"260","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":"104","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":"40% - 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":"0","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)"}}]}}