{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:02:30Z","timestamp":1743058950364,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030336066"},{"type":"electronic","value":"9783030336073"}],"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\/978-3-030-33607-3_52","type":"book-chapter","created":{"date-parts":[[2019,11,7]],"date-time":"2019-11-07T00:05:28Z","timestamp":1573085128000},"page":"486-493","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An Efficient Scheme for Prototyping kNN in the Context of Real-Time Human Activity Recognition"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6553-4220","authenticated-orcid":false,"given":"Paulo J. S.","family":"Ferreira","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0647-4675","authenticated-orcid":false,"given":"Ricardo M. C.","family":"Magalh\u00e3es","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1688-6769","authenticated-orcid":false,"given":"Kemilly Dearo","family":"Garcia","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7353-1799","authenticated-orcid":false,"given":"Jo\u00e3o M. P.","family":"Cardoso","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2471-2833","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Mendes-Moreira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,18]]},"reference":[{"key":"52_CR1","first-page":"31","volume":"2017","author":"S Zhang","year":"2017","unstructured":"Zhang, S., Wei, Z., Nie, J., Huang, L., Wang, S., Li, Z.: A review on human activity recognition using vision-based method. J. Healthc. Eng. 2017, 31 (2017). Article ID 3090343","journal-title":"J. Healthc. Eng."},{"issue":"1","key":"52_CR2","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"TM Cover","year":"1967","unstructured":"Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theory 13(1), 21\u201327 (1967)","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"3","key":"52_CR3","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1109\/TST.2014.6838194","volume":"19","author":"X Su","year":"2014","unstructured":"Su, X., Tong, H., Ji, P.: Activity recognition with smartphone sensors. Tsinghua Sci. Technol. 19(3), 235\u2013249 (2014)","journal-title":"Tsinghua Sci. Technol."},{"issue":"5","key":"52_CR4","doi-asserted-by":"publisher","first-page":"1608","DOI":"10.1016\/j.patcog.2014.11.015","volume":"48","author":"J Calvo-Zaragoza","year":"2015","unstructured":"Calvo-Zaragoza, J., Valero-Mas, J.J., Rico-Juan, R.J.: Improving kNN multi-label classification in Prototype Selection scenarios using class proposals. Pattern Recogn. 48(5), 1608\u20131622 (2015)","journal-title":"Pattern Recogn."},{"issue":"3","key":"52_CR5","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1109\/TPAMI.2011.142","volume":"34","author":"S Garcia","year":"2012","unstructured":"Garcia, S., Derrac, J., Cano, J., Herrera, F.: Prototype selection for nearest neighbor classification: taxonomy and empirical study. IEEE Trans. Pattern Anal. Mach. Intell. 34(3), 417\u2013435 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"52_CR6","first-page":"1601","volume":"11","author":"A Bifet","year":"2010","unstructured":"Bifet, A., Holmes, G., Kirkby, R., Pfahringer, B.: MOA: massive online analysis. J. Mach. Learn. Res. 11, 1601\u20131604 (2010)","journal-title":"J. Mach. Learn. Res."},{"key":"52_CR7","doi-asserted-by":"crossref","unstructured":"Reiss, A., Stricker, D.: Introducing a new benchmarked dataset for activity monitoring. In: The 16th IEEE International Symposium on Wearable Computers (ISWC) (2012)","DOI":"10.1109\/ISWC.2012.13"},{"key":"52_CR8","doi-asserted-by":"crossref","unstructured":"Bifet, A., Pfahringer, B., Read, J., Holmes, G.: Efficient data stream classification via probabilistic adaptive windows. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing, pp. 801\u2013806. ACM, March 2013","DOI":"10.1145\/2480362.2480516"},{"key":"52_CR9","doi-asserted-by":"crossref","unstructured":"Bifet, A., Gavalda, R.: Learning from time-changing data with adaptive windowing. In: Proceedings of the 2007 SIAM International Conference on Data Mining, pp. 443\u2013448. Society for Industrial and Applied Mathematics, April 2007","DOI":"10.1137\/1.9781611972771.42"},{"key":"52_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1007\/978-3-030-03493-1_63","volume-title":"Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2018","author":"KD Garcia","year":"2018","unstructured":"Garcia, K.D., de Carvalho, A.C.P.L.F., Mendes-Moreira, J.: A cluster-based prototype reduction for online classification. In: Yin, H., Camacho, D., Novais, P., Tall\u00f3n-Ballesteros, A. (eds.) IDEAL 2018. Lecture Notes in Computer Science, vol. 11314, pp. 603\u2013610. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-03493-1_63"},{"key":"52_CR11","doi-asserted-by":"crossref","unstructured":"Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, pp. 604\u2013613. ACM (1998)","DOI":"10.1145\/276698.276876"}],"container-title":["Lecture Notes in Computer Science","Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2019"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33607-3_52","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:59:46Z","timestamp":1710251986000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-33607-3_52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030336066","9783030336073"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33607-3_52","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"18 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDEAL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Data Engineering and Automated Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Manchester","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":"14 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ideal2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.confercare.manchester.ac.uk\/events\/ideal2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","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":"149","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":"94","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":"63% - 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":"2.5","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)"}}]}}