{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:00:28Z","timestamp":1740099628976,"version":"3.37.3"},"publisher-location":"Singapore","reference-count":8,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811527661"},{"type":"electronic","value":"9789811527678"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-981-15-2767-8_46","type":"book-chapter","created":{"date-parts":[[2020,1,25]],"date-time":"2020-01-25T15:02:35Z","timestamp":1579964555000},"page":"531-540","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction Model of Suspect Number Based on Deep Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4829-412X","authenticated-orcid":false,"given":"Chuyue","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2762-297X","authenticated-orcid":false,"given":"Manchun","family":"Cai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5190-6553","authenticated-orcid":false,"given":"Xiaofan","family":"Zhao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0888-0324","authenticated-orcid":false,"given":"Luzhe","family":"Cao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6322-6611","authenticated-orcid":false,"given":"Dawei","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,1,26]]},"reference":[{"issue":"5","key":"46_CR1","first-page":"99","volume":"2","author":"G Jin","year":"2016","unstructured":"Jin, G., Zhu, S., Lin, X.: Analysis and prediction of criminal situation in China (2017\u20132018). J. Chin. People\u2019s Public Secur. Univ. (Soc. Sci. Ed.) 2(5), 99\u2013110 (2016)","journal-title":"J. Chin. People\u2019s Public Secur. Univ. (Soc. Sci. Ed.)"},{"key":"46_CR2","first-page":"1703","volume":"26","author":"SA Asmai","year":"2014","unstructured":"Asmai, S.A., Roslin, N.I.A., Abdullah, R.W., et al.: Predictive crime mapping model using association rule mining for crime analysis. Sci. Int. 26, 1703\u20131706 (2014)","journal-title":"Sci. Int."},{"key":"46_CR3","doi-asserted-by":"publisher","first-page":"032031","DOI":"10.1088\/1742-6596\/1168\/3\/032031","volume":"1168","author":"Meilin Liu","year":"2019","unstructured":"Liu, M., Lu, T.: A hybrid model of crime prediction. J. Phys: Conf. Ser. 1168(3), 032031 (2019). https:\/\/doi.org\/10.1088\/1742-6596\/1168\/3\/032031","journal-title":"Journal of Physics: Conference Series"},{"issue":"2","key":"46_CR4","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1111\/j.1467-985X.2012.01056.x","volume":"176","author":"N Tollenaar","year":"2013","unstructured":"Tollenaar, N., van der Heijden, P.G.M.: Which method predicts recidivism best: a comparison of statistical, machine learning and data mining predictive models. J. Roy. Stat. Soc. 176(2), 565\u2013584 (2013)","journal-title":"J. Roy. Stat. Soc."},{"issue":"11","key":"46_CR5","first-page":"198","volume":"43","author":"R Li","year":"2017","unstructured":"Li, R., Sun, C., Ji, J.: Suspect characteristics prediction based on support vector machine. Comput. Eng. 43(11), 198\u2013203 (2017)","journal-title":"Comput. Eng."},{"issue":"9","key":"46_CR6","doi-asserted-by":"publisher","first-page":"2581","DOI":"10.1007\/s00521-016-2205-z","volume":"28","author":"MS Vural","year":"2017","unstructured":"Vural, M.S., G\u00f6k, M.: Criminal prediction using Naive Bayes theory. Neural Comput. Appl. 28(9), 2581\u20132592 (2017)","journal-title":"Neural Comput. Appl."},{"issue":"10","key":"46_CR7","first-page":"148","volume":"33","author":"F Sun","year":"2014","unstructured":"Sun, F., Cao, Z., Xiao, X.: Application of an improved random forest based classifier in crime prediction domain. J. Intell. 33(10), 148\u2013152 (2014)","journal-title":"J. Intell."},{"key":"46_CR8","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. Eprint Arxiv (2014)","DOI":"10.3115\/v1\/D14-1181"}],"container-title":["Communications in Computer and Information Science","Parallel Architectures, Algorithms and Programming"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-2767-8_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,25]],"date-time":"2020-01-25T15:09:45Z","timestamp":1579964985000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-2767-8_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811527661","9789811527678"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-2767-8_46","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"26 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Parallel Architectures, Algorithms and Programming","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"paap2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/sdcs.sysu.edu.cn\/paap2019","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"121","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":"39","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":"8","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":"32% - 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":"6","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)"}}]}}