{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:56:57Z","timestamp":1743116217534,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031329098"},{"type":"electronic","value":"9783031329104"}],"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\/978-3-031-32910-4_14","type":"book-chapter","created":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T05:38:34Z","timestamp":1683783514000},"page":"192-203","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Continuous Sub-prevalent Co-location Pattern Mining"],"prefix":"10.1007","author":[{"given":"Qilong","family":"Wang","sequence":"first","affiliation":[]},{"given":"Hongmei","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Lizhen","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,11]]},"reference":[{"issue":"3","key":"14_CR1","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/s10109-015-0216-4","volume":"17","author":"M Akbari","year":"2015","unstructured":"Akbari, M., Samadzadegan, F., Weibel, R.: A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollution. J. Geogr. Syst. 17(3), 249\u2013274 (2015)","journal-title":"J. Geogr. Syst."},{"issue":"14","key":"14_CR2","doi-asserted-by":"publisher","first-page":"11556","DOI":"10.1016\/j.eswa.2012.03.071","volume":"39","author":"P Phillips","year":"2012","unstructured":"Phillips, P., Lee, I.: Mining co-distribution patterns for large crime datasets. Expert Syst. Appl. 39(14), 11556\u201311563 (2012)","journal-title":"Expert Syst. Appl."},{"key":"14_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/978-3-030-73216-5_19","volume-title":"Database Systems for Advanced Applications. DASFAA 2021 International Workshops","author":"L Zeng","year":"2021","unstructured":"Zeng, L., Wang, L., Zeng, Y., Li, X., Xiao, Q.: Discovering spatial co-location patterns with dominant influencing features in anomalous regions. In: Jensen, C.S., et al. (eds.) DASFAA 2021. LNCS, vol. 12680, pp. 267\u2013282. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-73216-5_19"},{"issue":"12","key":"14_CR4","doi-asserted-by":"publisher","first-page":"1472","DOI":"10.1109\/TKDE.2004.90","volume":"16","author":"Y Huang","year":"2004","unstructured":"Huang, Y., Shekhar, S., Xiong, H.: Discovering co-location patterns from spatial data sets: a general approach. IEEE Trans. Knowl. Data Eng. 16(12), 1472\u20131485 (2004)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"10","key":"14_CR5","doi-asserted-by":"publisher","first-page":"1322","DOI":"10.1109\/TKDE.2008.97","volume":"20","author":"M Celik","year":"2008","unstructured":"Celik, M., Shekhar, S., Rogers, J.P., Shine, J.A.: Mixed-drove spatiotemporal co-occurrence pattern mining. IEEE Trans. Knowl. Data Eng. 20(10), 1322\u20131335 (2008)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"14_CR6","unstructured":"Li, X., Chen, H., Xiao, Q., Wang, L.: Spatiotemporal sub-prevalent co-location pattern mining. J. Southwest Univ. Nat. Sci. Ed. 42(11), 68\u201376 (2020)"},{"key":"14_CR7","unstructured":"Li, X.: Mining spatiotemporal sub-prevalent co-location patterns based on star model. Master\u2019s thesis, Yunnan University (2021)"},{"issue":"10","key":"14_CR8","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1109\/TKDE.2006.150","volume":"18","author":"JS Yoo","year":"2006","unstructured":"Yoo, J.S., Shekhar, S.: A joinless approach for mining spatial colocation patterns. IEEE Trans. Knowl. Data Eng. 18(10), 1323\u20131337 (2006)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Wang, L., Bao, Y., Lu, J., Yip, J.: A new join-less approach for co-location pattern mining. In: 2008 8th IEEE International Conference on Computer and Information Technology, pp. 197\u2013202. IEEE (2008)","DOI":"10.1109\/CIT.2008.4594673"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Wang, L., Bao, Y., Lu, Z.: Efficient discovery of spatial co-location patterns using the iCPI-tree. Open Inf. Syst. J. 3(1) (2009)","DOI":"10.2174\/1874133900903020069"},{"issue":"19","key":"14_CR11","doi-asserted-by":"publisher","first-page":"3370","DOI":"10.1016\/j.ins.2009.05.023","volume":"179","author":"L Wang","year":"2009","unstructured":"Wang, L., Zhou, L., Lu, J., Yip, J.: An order-clique-based approach for mining maximal co-locations. Inf. Sci. 179(19), 3370\u20133382 (2009)","journal-title":"Inf. Sci."},{"issue":"6","key":"14_CR12","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1360\/SSI-2020-0384","volume":"52","author":"P Yang","year":"2022","unstructured":"Yang, P., Wang, L., Wang, X., Zhou, L.: A spatial co-location pattern mining approach based on column calculation. Sci. Sin. Inf. 52(6), 1053\u20131068 (2022)","journal-title":"Sci. Sin. Inf."},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Andrzejewski, W., Boinski, P.: Maximal mixed-drove co-occurrence patterns. Inf. Syst. Front. 1\u201324 (2022)","DOI":"10.1007\/s10796-022-10344-8"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Qian, F., Yin, L., He, Q., He, J.: Mining spatio-temporal co-location patterns with weighted sliding window. In: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, vol. 3, pp. 181\u2013185. IEEE (2009)","DOI":"10.1109\/ICICISYS.2009.5358192"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Ma, Y., Lu, J., Yang, D.: Mining evolving spatial co-location patterns from spatio-temporal databases. In: 2022 IEEE International Conference on Big Data and Smart Computing (BigComp), pp. 129\u2013136. IEEE (2022)","DOI":"10.1109\/BigComp54360.2022.00034"},{"issue":"2","key":"14_CR16","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1007\/s12065-019-00332-4","volume":"13","author":"L Yang","year":"2020","unstructured":"Yang, L., Wang, L.: Mining traffic congestion propagation patterns based on spatio-temporal co-location patterns. Evol. Intel. 13(2), 221\u2013233 (2020)","journal-title":"Evol. Intel."},{"key":"14_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-319-68783-4_14","volume-title":"Web Information Systems Engineering \u2013 WISE 2017","author":"L Wang","year":"2017","unstructured":"Wang, L., Bao, X., Zhou, L., Chen, H.: Maximal sub-prevalent co-location patterns and efficient mining algorithms. In: Bouguettaya, A., et al. (eds.) WISE 2017. LNCS, vol. 10569, pp. 199\u2013214. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-68783-4_14"},{"issue":"5","key":"14_CR18","doi-asserted-by":"publisher","first-page":"1971","DOI":"10.1007\/s11280-018-0646-2","volume":"22","author":"L Wang","year":"2019","unstructured":"Wang, L., Bao, X., Zhou, L., Chen, H.: Mining maximal sub-prevalent co-location patterns. World Wide Web 22(5), 1971\u20131997 (2019)","journal-title":"World Wide Web"},{"issue":"2","key":"14_CR19","first-page":"465","volume":"40","author":"D Ma","year":"2020","unstructured":"Ma, D., Chen, H., Wang, L., Xiao, Q.: Dominant feature mining of spatial sub-prevalent co-location patterns. J. Comput. Appl. 40(2), 465\u2013472 (2020)","journal-title":"J. Comput. Appl."},{"key":"14_CR20","doi-asserted-by":"crossref","unstructured":"Xiong, K., Chen, H., Wang, L., Xiao, Q.: Mining fuzzy sub-prevalent co-location pattern with dominant feature. In: Proceedings of the 30th International Conference on Advances in Geographic Information Systems, pp. 1\u201310 (2022)","DOI":"10.1145\/3557915.3560971"}],"container-title":["Lecture Notes in Computer Science","Spatial Data and Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-32910-4_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T05:32:43Z","timestamp":1729402363000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-32910-4_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031329098","9783031329104"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-32910-4_14","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":"11 May 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SpatialDI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Spatial Data and Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanchang","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":"13 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"spatialdi2023","order":10,"name":"conference_id","label":"Conference ID","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":"68","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":"18","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":"26% - 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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}