{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T14:13:01Z","timestamp":1764079981226,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031466762"},{"type":"electronic","value":"9783031466779"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-46677-9_16","type":"book-chapter","created":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T13:02:29Z","timestamp":1699102949000},"page":"225-236","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Continuous Group Nearest Neighbor Query over\u00a0Sliding Window"],"prefix":"10.1007","author":[{"given":"Rui","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunhong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangpeng","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuanyu","family":"Zong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,5]]},"reference":[{"key":"16_CR1","doi-asserted-by":"crossref","unstructured":"Baig, F., Teng, D., Kong, J., Wang, F.: Spear: dynamic spatio-temporal query processing over high velocity data streams. In: 2021 IEEE 37th International Conference on Data Engineering (ICDE), pp. 2279\u20132284. IEEE (2021)","DOI":"10.1109\/ICDE51399.2021.00237"},{"issue":"10","key":"16_CR2","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/0898-1221(95)00153-P","volume":"30","author":"CK Ko\u00e7","year":"1995","unstructured":"Ko\u00e7, C.K.: Analysis of sliding window techniques for exponentiation. Comput. Math. Appl. 30(10), 17\u201324 (1995)","journal-title":"Comput. Math. Appl."},{"key":"16_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/3-540-48344-6_7","volume-title":"Spatio-Temporal Database Management","author":"G Kollios","year":"1999","unstructured":"Kollios, G., Gunopulos, D., Tsotras, V.J.: Nearest neighbor queries in a mobile environment. In: B\u00f6hlen, M.H., Jensen, C.S., Scholl, M.O. (eds.) STDBM 1999. LNCS, vol. 1678, pp. 119\u2013134. Springer, Heidelberg (1999). https:\/\/doi.org\/10.1007\/3-540-48344-6_7"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Kothuri, R.K.V., Ravada, S., Abugov, D.: Quadtree and r-tree indexes in oracle spatial: a comparison using gis data. In: Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, pp. 546\u2013557 (2002)","DOI":"10.1145\/564691.564755"},{"issue":"7","key":"16_CR5","doi-asserted-by":"publisher","first-page":"1175","DOI":"10.14778\/3450980.3450987","volume":"14","author":"T Li","year":"2021","unstructured":"Li, T., Chen, L., Jensen, C.S., Pedersen, T.B.: Trace: real-time compression of streaming trajectories in road networks. Proc. VLDB Endowment 14(7), 1175\u20131187 (2021)","journal-title":"Proc. VLDB Endowment"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Li, T., Chen, L., Jensen, C.S., Pedersen, T.B., Gao, Y., Hu, J.: Evolutionary clustering of moving objects. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 2399\u20132411. IEEE (2022)","DOI":"10.1109\/ICDE53745.2022.00225"},{"issue":"7","key":"16_CR7","doi-asserted-by":"publisher","first-page":"1050","DOI":"10.14778\/3384345.3384353","volume":"13","author":"T Li","year":"2020","unstructured":"Li, T., Huang, R., Chen, L., Jensen, C.S., Pedersen, T.B.: Compression of uncertain trajectories in road networks. Proc. VLDB Endowment 13(7), 1050\u20131063 (2020)","journal-title":"Proc. VLDB Endowment"},{"key":"16_CR8","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1007\/s10619-020-07317-8","volume":"39","author":"P Moutafis","year":"2021","unstructured":"Moutafis, P., Garc\u00eda-Garc\u00eda, F., Mavrommatis, G., Vassilakopoulos, M., Corral, A., Iribarne, L.: Algorithms for processing the group k nearest-neighbor query on distributed frameworks. Distrib. Parallel Databases 39, 733\u2013784 (2021)","journal-title":"Distrib. Parallel Databases"},{"key":"16_CR9","unstructured":"Papadias, D., Shen, Q., Tao, Y., Mouratidis, K.: Group nearest neighbor queries. In: Proceedings. 20th International Conference on Data Engineering, pp. 301\u2013312. IEEE (2004)"},{"key":"16_CR10","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/978-3-642-14246-8_33","volume-title":"Web-Age Information Management","author":"H Xu","year":"2010","unstructured":"Xu, H., Li, Z., Lu, Y., Deng, K., Zhou, X.: Group visible nearest neighbor queries in spatial databases. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds.) Web-Age Information Management, pp. 333\u2013344. Springer, Berlin Heidelberg, Berlin, Heidelberg (2010)"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Yang, D., Shastri, A., Rundensteiner, E.A., Ward, M.O.: An optimal strategy for monitoring top-k queries in streaming windows. In: Proceedings of the 14th International Conference on Extending Database Technology, pp. 57\u201368 (2011)","DOI":"10.1145\/1951365.1951375"},{"issue":"2","key":"16_CR12","first-page":"348","volume":"16","author":"J Yiying","year":"2022","unstructured":"Yiying, J., Liping, Z., Feihu, J., Xiaohong, H.: Groups nearest neighbor query of mixed data in spatial database. J. Front. Comput. Sci. Technol. 16(2), 348 (2022)","journal-title":"J. Front. Comput. Sci. Technol."},{"issue":"1","key":"16_CR13","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s11390-017-1708-0","volume":"32","author":"R Zhu","year":"2017","unstructured":"Zhu, R., Wang, B., Luo, S.Y., Yang, X.C., Wang, G.R.: Approximate continuous top-k query over sliding window. J. Comput. Sci. Technol. 32(1), 93\u2013109 (2017)","journal-title":"J. Comput. Sci. Technol."}],"container-title":["Lecture Notes in Computer Science","Advanced Data Mining and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-46677-9_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T13:23:09Z","timestamp":1699104189000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-46677-9_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031466762","9783031466779"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-46677-9_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"5 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ADMA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Data Mining and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenyang","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":"27 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"adma2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/adma2023.uqcloud.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes. Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"503","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":"216","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":"43% - 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":"2.97","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":"3.77","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}