{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T09:09:07Z","timestamp":1751533747406,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031212437"},{"type":"electronic","value":"9783031212444"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-21244-4_10","type":"book-chapter","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T20:06:23Z","timestamp":1668110783000},"page":"132-142","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Naive Bayes Classifier Based on\u00a0Neighborhood Granulation"],"prefix":"10.1007","author":[{"given":"Xingyu","family":"Fu","sequence":"first","affiliation":[]},{"given":"Yingyue","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Zhiyuan","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Yumin","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Nianfeng","family":"Zeng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"10_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2021.105456","volume":"135","author":"R Blanquero","year":"2021","unstructured":"Blanquero, R., Carrizosa, E., Ramirez-Cobo, P., Sillero-Denamiel, M.: Variable selection for Naive Bayes classification. Comput. Oper. Res. 135, 105456 (2021)","journal-title":"Comput. Oper. Res."},{"issue":"4","key":"10_CR2","doi-asserted-by":"publisher","first-page":"2729","DOI":"10.1007\/s00521-021-05989-6","volume":"34","author":"S Ruan","year":"2022","unstructured":"Ruan, S., Chen, B., Song, K., Li, H.: Weighted Naive Bayes text classification algorithm based on improved distance correlation coefficient. Neural. Comput. Appl. 34(4), 2729\u20132738 (2022)","journal-title":"Neural. Comput. Appl."},{"key":"10_CR3","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.patrec.2020.06.021","volume":"136","author":"H Kim","year":"2020","unstructured":"Kim, H., Park, J., Kim, D., Lee, J.: Multilabel Naive Bayes classification considering label dependence. Pattern Recognit. Lett. 136, 279\u2013285 (2020)","journal-title":"Pattern Recognit. Lett."},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1007\/s10100-021-00782-1","volume":"30","author":"R Blanquero","year":"2021","unstructured":"Blanquero, R., Carrizosa, E., Ramirez-Cobo, P., Sillero-Denamiel, M.: Constrained Naive Bayes with application to unbalanced data classification. Cent. Eur. J. Oper. Res. 30, 1403\u20131425 (2021)","journal-title":"Cent. Eur. J. Oper. Res."},{"key":"10_CR5","doi-asserted-by":"publisher","first-page":"5556992","DOI":"10.1155\/2021\/5556992","volume":"2021","author":"Y Xiong","year":"2021","unstructured":"Xiong, Y., Ye, M., Wu, C.: Cancer classification with a cost-sensitive Naive Bayes stacking ensemble. Comput. Math. Methods Med. 2021, 5556992 (2021)","journal-title":"Comput. Math. Methods Med."},{"issue":"1","key":"10_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13634-021-00742-6","volume":"2021","author":"H Chen","year":"2021","unstructured":"Chen, H., Hu, S., Hua, R., Zhao, X.: Improved naive Bayes classification algorithm for traffic risk management. EURASIP J. Adv. Sig. Process. 2021(1), 1\u201312 (2021). https:\/\/doi.org\/10.1186\/s13634-021-00742-6","journal-title":"EURASIP J. Adv. Sig. Process."},{"key":"10_CR7","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.patcog.2018.11.032","volume":"88","author":"L Jiang","year":"2019","unstructured":"Jiang, L., Zhang, L., Yu, L., Wang, D.: Class-specific attribute weighted Naive Bayes. Pattern Recognit. 88, 321\u2013330 (2019)","journal-title":"Pattern Recognit."},{"key":"10_CR8","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","volume":"8","author":"LA Zadeh","year":"1965","unstructured":"Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338\u2013353 (1965)","journal-title":"Inf. Control"},{"key":"10_CR9","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/BF01001956","volume":"11","author":"Z Pawlak","year":"1982","unstructured":"Pawlak, Z.: Rough sets. Int. J. Comput. Inf. Sci. 11, 341\u2013356 (1982)","journal-title":"Int. J. Comput. Inf. Sci."},{"issue":"3","key":"10_CR10","doi-asserted-by":"publisher","first-page":"2067","DOI":"10.1007\/s10462-020-09899-2","volume":"54","author":"S Guo","year":"2021","unstructured":"Guo, S., Zhao, H.: Hierarchical classification with multi-path selection based on granular computing. Artif. Intell. Rev. 54(3), 2067\u20132089 (2021)","journal-title":"Artif. Intell. Rev."},{"key":"10_CR11","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1016\/j.ins.2020.05.101","volume":"537","author":"Y Chen","year":"2020","unstructured":"Chen, Y., Miao, D.: Granular regression with a gradient descent method. Inf. Sci. 537, 246\u2013260 (2020)","journal-title":"Inf. Sci."},{"key":"10_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106880","volume":"219","author":"N Liu","year":"2021","unstructured":"Liu, N., Xu, Z., Wu, H., Ren, P.: Conversion-based aggregation algorithms for linear ordinal rankings combined with granular computing. Knowl. Based Syst. 219, 106880 (2021)","journal-title":"Knowl. Based Syst."},{"key":"10_CR13","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1016\/j.ins.2018.05.053","volume":"507","author":"J Zhou","year":"2020","unstructured":"Zhou, J., Lai, Z., Miao, D., Gao, C., Yue, X.: Multigranulation rough-fuzzy clustering based on shadowed sets. Inf. Sci. 507, 553\u2013573 (2020)","journal-title":"Inf. Sci."},{"issue":"2","key":"10_CR14","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1109\/TCYB.2014.2361772","volume":"46","author":"W Xu","year":"2016","unstructured":"Xu, W., Li, W.: Granular computing approach to two-way learning based on formal concept analysis in fuzzy datasets. IEEE Trans. Cybern. 46(2), 336\u2013379 (2016)","journal-title":"IEEE Trans. Cybern."},{"key":"10_CR15","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.engappai.2016.02.002","volume":"52","author":"L Jing","year":"2016","unstructured":"Jing, L., Li, C., Wang, S., Zhang, L.: Deep feature weighting for Naive Bayes and its application to text classification. Eng. Appl. Artif. Intell. 52, 26\u201339 (2016)","journal-title":"Eng. Appl. Artif. Intell."}],"container-title":["Lecture Notes in Computer Science","Rough Sets"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21244-4_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T17:05:37Z","timestamp":1709831137000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21244-4_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031212437","9783031212444"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21244-4_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"11 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IJCRS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Joint Conference on Rough Sets","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Suzhou","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ijcrs2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ijcrs2022.cn\/","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":"Easy chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"42","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":"28","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":"67% - 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":"2","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)"}}]}}