{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T23:37:59Z","timestamp":1769989079478,"version":"3.49.0"},"publisher-location":"Cham","reference-count":8,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030864712","type":"print"},{"value":"9783030864729","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-86472-9_17","type":"book-chapter","created":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T22:02:41Z","timestamp":1630360961000},"page":"185-191","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["EHUCM: An Efficient Algorithm for Mining High Utility Co-location Patterns from Spatial Datasets with Feature-specific Utilities"],"prefix":"10.1007","author":[{"given":"Yinqiao","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lizhen","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peizhong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junyi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"17_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TKDE.2021.3060119","volume":"4347","author":"P Yang","year":"2021","unstructured":"Yang, P., Wang, L., Wang, X., Zhou, L.: SCPM-CR: a novel method for spatial co-location pattern mining with coupling relation consideration. IEEE Trans. Knowl. Data Eng. 4347, 1\u201314 (2021). https:\/\/doi.org\/10.1109\/TKDE.2021.3060119","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"17_CR2","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1016\/j.eswa.2015.10.010","volume":"46","author":"W Yu","year":"2016","unstructured":"Yu, W.: Spatial co-location pattern mining for location-based services in road networks. Exp. Syst. Appl. 46, 324\u2013335 (2016). https:\/\/doi.org\/10.1016\/j.eswa.2015.10.010","journal-title":"Exp. Syst. Appl."},{"issue":"3","key":"17_CR3","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). https:\/\/doi.org\/10.1007\/s10109-015-0216-4","journal-title":"J. Geogr. Syst."},{"key":"17_CR4","doi-asserted-by":"publisher","first-page":"333","DOI":"10.3233\/IDA-173752","volume":"23","author":"JS Yoo","year":"2019","unstructured":"Yoo, J.S., Bow, M.: A framework for generating condensed co-location sets from spatial databases. Intell. Data Anal. 23, 333\u2013355 (2019). https:\/\/doi.org\/10.3233\/IDA-173752","journal-title":"Intell. Data Anal."},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Truong, T., Duong, H., Le, B., Fournier-Viger, P.: Efficient algorithms for mining frequent high utility sequences with constraints. Inf. Sci. (Ny). 568, 239\u2013264 (2021)","DOI":"10.1016\/j.ins.2021.01.060"},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Yang, S., Wang, L.: A framework for mining spatial high utility co-location patterns. In: The 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2015), pp. 595\u2013601. IEEE Press, New York (2015)","DOI":"10.1109\/FSKD.2015.7382010"},{"key":"17_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1007\/978-3-319-55699-4_28","volume-title":"Database Systems for Advanced Applications","author":"L Wang","year":"2017","unstructured":"Wang, L., Jiang, W., Chen, H., Fang, Y.: Efficiently mining high utility co-location patterns from spatial data sets with instance-specific utilities. In: Candan, S., Chen, L., Pedersen, T.B., Chang, L., Hua, W. (eds.) DASFAA 2017. LNCS, vol. 10178, pp. 458\u2013474. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-55699-4_28"},{"key":"17_CR8","first-page":"1721","volume":"42","author":"X Wang","year":"2019","unstructured":"Wang, X., Wang, L., et al.: Mining spatial high utility co-location patterns based on feature utility ratio. Chin. J. Comput. 42, 1721\u20131738 (2019)","journal-title":"Chin. J. Comput."}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86472-9_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T12:23:39Z","timestamp":1725711819000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86472-9_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030864712","9783030864729"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86472-9_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"31 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEXA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database and Expert Systems Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/dexa2021","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":"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":"37","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":"31","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":"25% - 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":"4","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":"5","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)"}},{"value":"DEXA 2021 Workshops: 50 papers submitted, 23 papers accepted","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}