{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T12:03:16Z","timestamp":1768737796528,"version":"3.49.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T00:00:00Z","timestamp":1649462400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T00:00:00Z","timestamp":1649462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Deanship of Scientific Research at Umm Al-Qura University","award":["19-COM-1-01-0023"],"award-info":[{"award-number":["19-COM-1-01-0023"]}]},{"name":"faculty research support fund NUCES"},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s10489-021-03072-0","type":"journal-article","created":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T22:11:20Z","timestamp":1649542280000},"page":"18131-18155","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Image blurring and sharpening inspired three-way clustering approach"],"prefix":"10.1007","volume":"52","author":[{"given":"Anwar","family":"Shah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5606-1481","authenticated-orcid":false,"given":"Nouman","family":"Azam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eisa","family":"Alanazi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JingTao","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,9]]},"reference":[{"key":"3072_CR1","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.ijar.2019.11.011","volume":"118","author":"MK Afridi","year":"2020","unstructured":"Afridi MK, Azam N, Yao JT (2020) Variance based three-way clustering approaches for handling overlapping clustering. International Journal of Approximate Reasoning 118:47\u201363","journal-title":"International Journal of Approximate Reasoning"},{"key":"3072_CR2","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.ijar.2018.04.001","volume":"98","author":"MK Afridi","year":"2018","unstructured":"Afridi MK, Azam N, Yao JT, Alanazi E (2018) A three-way clustering approach for handling missing data using GTRS. International Journal of Approximate Reasoning 98:11\u201324","journal-title":"International Journal of Approximate Reasoning"},{"key":"3072_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ijar.2020.12.003","volume":"130","author":"B Ali","year":"2021","unstructured":"Ali B, Azam N, Shah A, Yao JT (2021) A spatial filtering inspired three-way clustering approach with application to outlier detection. International Journal of Approximate Reasoning 130:1\u201321","journal-title":"International Journal of Approximate Reasoning"},{"key":"3072_CR4","unstructured":"Bache K, Lichman M (2013) UCI machine learning repository http:\/\/archive.ics.uci.edu\/ml (retrieved: 2021-01-02)"},{"key":"3072_CR5","doi-asserted-by":"crossref","unstructured":"Bendale A, Boult T (2015) Towards open world recognition. In: Proceedings of the Conference on Computer Vision and Pattern Recognition. pp. 1893\u20131902","DOI":"10.1109\/CVPR.2015.7298799"},{"issue":"2\u20133","key":"3072_CR6","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/0098-3004(84)90020-7","volume":"10","author":"JC Bezdek","year":"1984","unstructured":"Bezdek JC, Ehrlich R, Full W (1984) Fcm: The fuzzy c-means clustering algorithm. Computers and Geosciences 10(2\u20133):191\u2013203","journal-title":"Computers and Geosciences"},{"key":"3072_CR7","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.knosys.2019.05.018","volume":"180","author":"A Campagner","year":"2019","unstructured":"Campagner A, Ciucci D (2019) Orthopartitions and soft clustering: soft mutual information measures for clustering validation. Knowledge-Based Systems 180:51\u201361","journal-title":"Knowledge-Based Systems"},{"issue":"4","key":"3072_CR8","doi-asserted-by":"publisher","first-page":"2923","DOI":"10.1016\/j.eswa.2010.06.052","volume":"38","author":"M Chen","year":"2011","unstructured":"Chen M, Miao D (2011) Interval set clustering. Expert Systems with Applications 38(4):2923\u20132932","journal-title":"Expert Systems with Applications"},{"key":"3072_CR9","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.ins.2020.05.039","volume":"535","author":"X Chu","year":"2020","unstructured":"Chu X, Sun B, Li X, Han K, Wu J, Zhang Y, Huang Q (2020) Neighborhood rough set-based three-way clustering considering attribute correlations: an approach to classification of potential gout groups. Information Sciences 535:28\u201341","journal-title":"Information Sciences"},{"key":"3072_CR10","doi-asserted-by":"crossref","unstructured":"Fei G, Liu B (2016) Breaking the closed world assumption in text classification. In: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies pp 506\u2013514","DOI":"10.18653\/v1\/N16-1061"},{"key":"3072_CR11","unstructured":"Fr\u00e4nti P, Sieranoja S (2018) clustering datasets, http:\/\/cs.joensuu.fi\/sipu\/datasets\/ (retrieved: 2020-11-22) (2018)"},{"key":"3072_CR12","doi-asserted-by":"crossref","unstructured":"Ge Z, Demyanov S, Chen Z, Garnavi R (2017) Generative openmax for multi-class open set classification. In: Proceedings of the British Machine Vision Conference - Royal Geographic Society of London","DOI":"10.5244\/C.31.42"},{"issue":"10","key":"3072_CR13","doi-asserted-by":"publisher","first-page":"3614","DOI":"10.1109\/TPAMI.2020.2981604","volume":"43","author":"G Geng","year":"2020","unstructured":"Geng G, Huang SJ, Chen S (2020) Recent advances in open set recognition: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 43(10):3614\u20133631","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"3072_CR14","unstructured":"Gonzalez RC, Wintz P (2018) Digital image processing, fourth edition. Addison-Wesley Publishing"},{"issue":"3","key":"3072_CR15","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/s10994-016-5610-8","volume":"106","author":"PRM J\u00fanior","year":"2017","unstructured":"J\u00fanior PRM, DeSouza RM, Werneck RDO, Stein BV, Pazinato DV, Almeida WRD, Penatti OA, Torres RDS, Rocha A (2017) Nearest neighbors distance ratio open-set classifier. Machine Learning 106(3):359\u2013386","journal-title":"Machine Learning"},{"key":"3072_CR16","doi-asserted-by":"publisher","first-page":"244","DOI":"10.1016\/j.ins.2016.04.051","volume":"378","author":"J Li","year":"2017","unstructured":"Li J, Huang C, Qi J, Qian Y, Liu W (2017) Three-way cognitive concept learning via multi-granularity. Information sciences 378:244\u2013263","journal-title":"Information sciences"},{"issue":"2","key":"3072_CR17","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1016\/S0031-3203(02)00060-2","volume":"36","author":"A Likas","year":"2003","unstructured":"Likas A, Vlassis N, Verbeek JJ (2003) The global k-means clustering Algorithm. Pattern Recognition 36(2):451\u2013461","journal-title":"Pattern Recognition"},{"issue":"1","key":"3072_CR18","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/B:JIIS.0000029668.88665.1a","volume":"23","author":"P Lingras","year":"2004","unstructured":"Lingras P, West C (2004) Interval set clustering of web users with rough k-means. Journal of Intelligent Information Systems 23(1):5\u201316","journal-title":"Journal of Intelligent Information Systems"},{"issue":"11","key":"3072_CR19","doi-asserted-by":"publisher","first-page":"205","DOI":"10.21105\/joss.00205","volume":"2","author":"L McInnes","year":"2017","unstructured":"McInnes L, Healy J, Astels S (2017) hdbscan: Hierarchical density based clustering. Journal of Open Source Software 2(11):205","journal-title":"Journal of Open Source Software"},{"key":"3072_CR20","doi-asserted-by":"crossref","unstructured":"Mundt M, Pliushch I, Majumder S, Ramesh V (2019) Open set recognition through deep neural network uncertainty: Does out-of-distribution detection require generative classifiers? In: Proceedings of International Conference on Computer Vision Workshops pp 753\u2013757","DOI":"10.1109\/ICCVW.2019.00098"},{"key":"3072_CR21","unstructured":"Ng AY, Jordan MI, Weiss Y (2002) On spectral clustering: Analysis and an algorithm. In: Proceedings of the Conference on Advances in Neural Information Processing Systems. pp 849\u2013856"},{"issue":"1","key":"3072_CR22","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1109\/3477.658584","volume":"28","author":"W Pedrycz","year":"1998","unstructured":"Pedrycz W (1998) Shadowed sets: representing and processing fuzzy sets. IEEE Transactions on Systems, Man, and Cybernetics, Part B 28(1):103\u2013109","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part B"},{"key":"3072_CR23","doi-asserted-by":"crossref","unstructured":"Perera P, Morariu VI, Jain R, Manjunatha V, Wigington C, Ordonez V, Patel VM (2020) Generative-discriminative feature representations for open-set recognition. In: Proceedings of the Computer Vision and Pattern Recognition. pp 11814\u201311823","DOI":"10.1109\/CVPR42600.2020.01183"},{"issue":"6191","key":"3072_CR24","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez A, Laio A (2014) Clustering by fast search and find of density peaks. Science 344(6191):1492\u20131496","journal-title":"Science"},{"issue":"7","key":"3072_CR25","doi-asserted-by":"publisher","first-page":"1757","DOI":"10.1109\/TPAMI.2012.256","volume":"35","author":"WJ Scheirer","year":"2012","unstructured":"Scheirer WJ, Rocha ADR, Sapkota A, Boult TE (2012) Toward open set recognition. IEEE transactions on pattern analysis and machine intelligence 35(7):1757\u20131772","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"3072_CR26","doi-asserted-by":"crossref","unstructured":"Shu L, Xu H, Liu B (2017) Doc: Deep open classification of text documents. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing pp 2911\u20132916","DOI":"10.18653\/v1\/D17-1314"},{"issue":"2","key":"3072_CR27","doi-asserted-by":"publisher","first-page":"59","DOI":"10.3390\/info10020059","volume":"10","author":"P Wang","year":"2019","unstructured":"Wang P, Liu Q, Xu G, Wang K (2019) A three-way clustering method based on ensemble strategy and three-way decision. Information 10(2):59","journal-title":"Information"},{"issue":"10","key":"3072_CR28","doi-asserted-by":"publisher","first-page":"2767","DOI":"10.1007\/s13042-018-0901-y","volume":"10","author":"P Wang","year":"2019","unstructured":"Wang P, Shi H, Yang X, Mi J (2019) Three-way kmeans: integrating k-means and three-way decision. International Journal of Machine Learning and Cybernetics 10(10):2767\u20132777","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"3072_CR29","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.knosys.2018.04.029","volume":"155","author":"P Wang","year":"2018","unstructured":"Wang P, Yao YY (2018) Ce3: A three-way clustering method based on mathematical morphology. Knowledge-Based Systems 155:54\u201365","journal-title":"Knowledge-Based Systems"},{"key":"3072_CR30","first-page":"379","volume":"12117","author":"J Xiong","year":"2018","unstructured":"Xiong J, Yu H (2018) An adaptive three-way clustering algorithm for mixed-type data. Proceedings of the International Symposium on Methodologies for Intelligent Systems, Lecture Notes in Computer Science 12117:379\u2013388","journal-title":"Proceedings of the International Symposium on Methodologies for Intelligent Systems, Lecture Notes in Computer Science"},{"key":"3072_CR31","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.patcog.2018.07.030","volume":"85","author":"Y Yang","year":"2019","unstructured":"Yang Y, Hou C, Lang Y, Guan D, Huang D, Xu J (2019) Open-set human activity recognition based on micro-doppler signatures. Pattern Recognition 85:60\u201369","journal-title":"Pattern Recognition"},{"key":"3072_CR32","unstructured":"Yao YY (2019) Tri-level thinking: models of three-way decision. International Journal of Machine Learning and Cybernetics pp 1\u201313"},{"issue":"6","key":"3072_CR33","doi-asserted-by":"publisher","first-page":"1080","DOI":"10.1016\/j.ins.2010.11.019","volume":"181","author":"YY Yao","year":"2011","unstructured":"Yao YY (2011) The superiority of three-way decisions in probabilistic rough set models. Information Sciences 181(6):1080\u20131096","journal-title":"Information Sciences"},{"key":"3072_CR34","first-page":"1","volume":"7413","author":"YY Yao","year":"2012","unstructured":"Yao YY (2012) An outline of a theory of three-way decisions. Proceedings of the International Conference on Rough Sets and Current Trends in Computing, Lecture Notes in Computer Science 7413:1\u201317","journal-title":"Proceedings of the International Conference on Rough Sets and Current Trends in Computing, Lecture Notes in Computer Science"},{"key":"3072_CR35","first-page":"62","volume":"9436","author":"YY Yao","year":"2015","unstructured":"Yao YY (2015) Rough sets and three-way decisions. Proceedings of the International Conference on Rough Sets and Knowledge Technology, Lecture Notes in Computer Science 9436:62\u201373","journal-title":"Proceedings of the International Conference on Rough Sets and Knowledge Technology, Lecture Notes in Computer Science"},{"key":"3072_CR36","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.ijar.2018.09.005","volume":"103","author":"YY Yao","year":"2018","unstructured":"Yao YY (2018) Three-way decision and granular computing. International Journal of Approximate Reasoning 103:107\u2013123","journal-title":"International Journal of Approximate Reasoning"},{"issue":"1","key":"3072_CR37","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s41066-020-00211-9","volume":"6","author":"YY Yao","year":"2021","unstructured":"Yao YY (2021) Set-theoretic models of three-way decision. Granular Computing 6(1):133\u2013148","journal-title":"Granular Computing"},{"key":"3072_CR38","first-page":"300","volume":"10314","author":"H Yu","year":"2017","unstructured":"Yu H (2017) A framework of three-way cluster analysis. Proceedings of the International Joint Conference on Rough Sets, Lecture Notes in Computer Science 10314:300\u2013312","journal-title":"Proceedings of the International Joint Conference on Rough Sets, Lecture Notes in Computer Science"},{"issue":"5","key":"3072_CR39","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.1007\/s13042-019-00988-5","volume":"11","author":"H Yu","year":"2020","unstructured":"Yu H, Chang Z, Wang G, Chen X (2020) An efficient three-way clustering algorithm based on gravitational search. International Journal of Machine Learning and Cybernetics 11(5):1003\u20131016","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"3072_CR40","doi-asserted-by":"crossref","unstructured":"Yu H, Chang Z, Zhou B (2017) A novel three-way clustering algorithm for mixed-type data. In: Proceedings of International Conference on Big Knowledge. pp 119\u2013126","DOI":"10.1109\/ICBK.2017.38"},{"key":"3072_CR41","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.ijar.2019.09.001","volume":"115","author":"H Yu","year":"2019","unstructured":"Yu H, Chen Y, Lingras P, Wang G (2019) A three-way cluster ensemble approach for large-scale data. International Journal of Approximate Reasoning 115:32\u201349","journal-title":"International Journal of Approximate Reasoning"},{"issue":"1","key":"3072_CR42","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.ijar.2013.03.018","volume":"55","author":"H Yu","year":"2014","unstructured":"Yu H, Liu Z, Wang G (2014) An automatic method to determine the number of clusters using decision-theoretic rough set. International Journal of Approximate Reasoning 55(1):101\u2013115","journal-title":"International Journal of Approximate Reasoning"},{"key":"3072_CR43","first-page":"765","volume":"8818","author":"H Yu","year":"2014","unstructured":"Yu H, Su T, Zeng X (2014) A three-way decisions clustering algorithm for incomplete data. Proceedings of the International Conference on Rough Sets and Knowledge Technology, Lecture Notes in Computer Science, Lecture Notes in Computer Science 8818:765\u2013776","journal-title":"Proceedings of the International Conference on Rough Sets and Knowledge Technology, Lecture Notes in Computer Science, Lecture Notes in Computer Science"},{"key":"3072_CR44","first-page":"313","volume":"10314","author":"H Yu","year":"2017","unstructured":"Yu H, Wang X, Wang G (2017) A semi-supervised three-way clustering framework for multi-view data. Proceedings of the International Joint Conference on Rough Sets, Lecture Notes in Computer Science 10314:313\u2013325","journal-title":"Proceedings of the International Joint Conference on Rough Sets, Lecture Notes in Computer Science"},{"key":"3072_CR45","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1016\/j.ins.2018.03.009","volume":"507","author":"H Yu","year":"2020","unstructured":"Yu H, Wang X, Wang G, Zeng X (2020) An active three-way clustering method via low-rank matrices for multi-view data. Information Sciences 507:823\u2013839","journal-title":"Information Sciences"},{"key":"3072_CR46","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.knosys.2015.05.028","volume":"91","author":"H Yu","year":"2016","unstructured":"Yu H, Zhang C, Wang G (2016) A tree-based incremental overlapping clustering method using the three-way decision theory. Knowledge-Based Systems 91:189\u2013203","journal-title":"Knowledge-Based Systems"},{"key":"3072_CR47","doi-asserted-by":"crossref","unstructured":"Yu H, Chen L, Yao JT (2020) A three-way density peak clustering method based on evidence theory. Knowledge-Based Systems, pp 106532","DOI":"10.1016\/j.knosys.2020.106532"},{"key":"3072_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2019.122289","volume":"535","author":"H Yu","year":"2019","unstructured":"Yu H, Chen L, Yao JT, Wang X (2019) A three-way clustering method based on an improved dbscan algorithm. Physica A: Statistical Mechanics and its Applications 535:122289","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"3072_CR49","doi-asserted-by":"crossref","unstructured":"Zhang C, Gao R, Qin H, Feng X (2021) Three-way clustering method for incomplete information system based on set-pair analysis. Granular Computing, pp 1\u201310","DOI":"10.1007\/s41066-019-00197-z"},{"issue":"8","key":"3072_CR50","doi-asserted-by":"publisher","first-page":"1690","DOI":"10.1109\/TPAMI.2016.2613924","volume":"39","author":"H Zhang","year":"2016","unstructured":"Zhang H, Patel VM (2016) Sparse representation-based open set recognition. IEEE transactions on pattern analysis and machine intelligence 39(8):1690\u20131696","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"3072_CR51","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.ijar.2018.10.019","volume":"105","author":"Y Zhang","year":"2019","unstructured":"Zhang Y, Miao D, Wang J, Zhang Z (2019) A cost-sensitive three-way combination technique for ensemble learning in sentiment classification. International Journal of Approximate Reasoning 105:85\u201397","journal-title":"International Journal of Approximate Reasoning"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-03072-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-021-03072-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-03072-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,19]],"date-time":"2022-11-19T10:39:19Z","timestamp":1668854359000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-021-03072-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,9]]},"references-count":51,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["3072"],"URL":"https:\/\/doi.org\/10.1007\/s10489-021-03072-0","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,9]]},"assertion":[{"value":"2 December 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}