{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:12:09Z","timestamp":1760609529972,"version":"3.37.3"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2023,5,14]],"date-time":"2023-05-14T00:00:00Z","timestamp":1684022400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,5,14]],"date-time":"2023-05-14T00:00:00Z","timestamp":1684022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006099","62076111"],"award-info":[{"award-number":["62006099","62076111"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s10462-023-10499-z","type":"journal-article","created":{"date-parts":[[2023,5,15]],"date-time":"2023-05-15T12:57:55Z","timestamp":1684155475000},"page":"12201-12232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Gift: granularity over specific-class for feature selection"],"prefix":"10.1007","volume":"56","author":[{"given":"Jing","family":"Ba","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keyu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xibei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhua","family":"Qian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,5,14]]},"reference":[{"issue":"20","key":"10499_CR1","doi-asserted-by":"crossref","first-page":"2627","DOI":"10.3390\/math9202627","volume":"9","author":"F Abukhodair","year":"2021","unstructured":"Abukhodair F, Alsaggaf W, Jamal AT, Abdel-Khalek S, Mansour RF (2021) An intelligent metaheuristic binary pigeon optimization-based feature selection and big data classification in a mapreduce environment. Mathematics 9(20):2627","journal-title":"Mathematics"},{"key":"10499_CR2","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.patcog.2018.07.023","volume":"84","author":"B Biggio","year":"2018","unstructured":"Biggio B, Roli F (2018) Wild patterns: ten years after the rise of adversarial machine learning. Pattern Recog 84:317\u2013331","journal-title":"Pattern Recog"},{"key":"10499_CR3","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.ins.2015.03.039","volume":"313","author":"FL Cao","year":"2015","unstructured":"Cao FL, Ye HL, Wang DH (2015) A probabilistic learning algorithm for robust modeling using neural networks with random weights. Info Sci 313:62\u201378","journal-title":"Info Sci"},{"key":"10499_CR4","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.ins.2020.05.010","volume":"535","author":"Y Chen","year":"2020","unstructured":"Chen Y, Liu KY, Song JJ, Fujita H, Yang XB, Qian YH (2020) Attribute group for attribute reduction. Info Sci 535:64\u201380","journal-title":"Info Sci"},{"key":"10499_CR5","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J (2006) Statistical comparisons of classifiers over multiple datasets. J Machine Learn Res 7:1\u201330","journal-title":"J Machine Learn Res"},{"key":"10499_CR6","doi-asserted-by":"crossref","first-page":"109111","DOI":"10.1016\/j.patcog.2022.109111","volume":"134","author":"WF Gao","year":"2023","unstructured":"Gao WF, Hao PT, Wu Y, Zhang P (2023) A unified low-order information-theoretic feature selection framework for multi-label learning. Pattern Recog 134","journal-title":"Pattern Recog"},{"key":"10499_CR7","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/j.eswa.2006.10.043","volume":"34","author":"QH Hu","year":"2008","unstructured":"Hu QH, Yu DR, Xie ZX (2008) Neighborhood classifiers. Exp Syst Appl 34:866\u2013876","journal-title":"Exp Syst Appl"},{"key":"10499_CR8","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.ins.2022.02.024","volume":"593","author":"L Hu","year":"2022","unstructured":"Hu L, Gao L, Li Y, Zhang P, Gao W (2022) Feature-specific mutual information variation for multi-label feature selection. Info Sci 593:449\u2013471","journal-title":"Info Sci"},{"key":"10499_CR9","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.ins.2016.09.061","volume":"375","author":"GX Jiang","year":"2017","unstructured":"Jiang GX, Wang WJ (2017) Markov cross-validation for time series model evaluations. Info Sci 375:219\u2013233","journal-title":"Info Sci"},{"key":"10499_CR10","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1023\/A:1008280620621","volume":"7","author":"I Kononenko","year":"1997","unstructured":"Kononenko I, \u0160imec E, Robnik-\u0160ikonja M (1997) Overcoming the myopia of inductive learning algorithms with reliefF. Appl Intell 7:39\u201355","journal-title":"Appl Intell"},{"key":"10499_CR11","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.knosys.2018.05.019","volume":"162","author":"GM Lang","year":"2018","unstructured":"Lang GM, Cai MJ, Fujita H, Xiao QM (2018) Related families-based attribute reduction of dynamic covering decision information systems. Knowl Based Syst 162:161\u2013173","journal-title":"Knowl Based Syst"},{"key":"10499_CR12","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.knosys.2015.07.024","volume":"91","author":"JH Li","year":"2016","unstructured":"Li JH, Ren Y, Mei CL, Qian YH, Yang XB (2016) A comparative study of multigranulation rough sets and concept lattices via rule acquisition. Knowl Based Syst 91:152\u2013164","journal-title":"Knowl Based Syst"},{"key":"10499_CR13","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.patcog.2017.02.025","volume":"67","author":"F Li","year":"2017","unstructured":"Li F, Miao DQ, Pedrycz W (2017) Granular multi-label feature selection based on mutual information. Pattern Recog 67:410\u2013423","journal-title":"Pattern Recog"},{"key":"10499_CR14","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1142\/S0218488504002631","volume":"12","author":"JY Liang","year":"2004","unstructured":"Liang JY, Shi ZZ (2004) The information entropy, rough entropy and knowledge granulation in rough set theory. Int J Uncertain Fuzz Knowl Based Syst 12:37\u201346","journal-title":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems"},{"key":"10499_CR15","doi-asserted-by":"crossref","first-page":"912","DOI":"10.1016\/j.ijar.2012.02.004","volume":"53","author":"JY Liang","year":"2012","unstructured":"Liang JY, Wang F, Dang CY, Qian YH (2012) An efficient rough feature selection algorithm with a multi-granulation view. Int J Approx Reason 53:912\u2013926","journal-title":"Int J Approx Reason"},{"key":"10499_CR16","doi-asserted-by":"crossref","first-page":"108039","DOI":"10.1016\/j.patcog.2021.108039","volume":"118","author":"GF Lin","year":"2021","unstructured":"Lin GF, Kang XB, Liao KY, Chen YJ (2021) Deep graph learning for semi-supervised classification. Pattern Recog 118:108039","journal-title":"Pattern Recog"},{"key":"10499_CR17","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.knosys.2018.11.034","volume":"165","author":"KY Liu","year":"2019","unstructured":"Liu KY, Yang XB, Yu HL, Mi JS, Wang PX, Chen XJ (2019) Rough set based semi-supervised feature selection via ensemble selector. Knowl Based Syst 165:282\u2013296","journal-title":"Knowl Based Syst"},{"key":"10499_CR18","doi-asserted-by":"crossref","first-page":"2149","DOI":"10.1007\/s13042-020-01107-5","volume":"11","author":"KY Liu","year":"2020","unstructured":"Liu KY, Yang X, Yu H, Fujita H, Chen X, Liu D (2020) Supervised information granulation strategy for attribute reduction. Int J Machine Learn Cybern 11:2149\u20132163","journal-title":"Int J Machine Learn Cybern"},{"key":"10499_CR19","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2023.3255893","author":"KY Liu","year":"2023","unstructured":"Liu KY, Li TR, Yang XB, Chen HM, Wang J, Deng ZX (2023) SemiFREE: semi-supervised feature selection with fuzzy relevance and redundancy. IEEE Trans Fuzz Syst. https:\/\/doi.org\/10.1109\/TFUZZ.2023.3255893","journal-title":"IEEE Trans Fuzz Syst"},{"key":"10499_CR20","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1007\/s00500-017-2879-x","volume":"23","author":"F Min","year":"2019","unstructured":"Min F, Liu FL, Wen LY, Zhang ZH (2019) Tri-partition cost-sensitive active learning through KNN. Soft Comput 23:1557\u20131572","journal-title":"Soft Comput"},{"key":"10499_CR21","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.ins.2021.10.065","volume":"584","author":"JJ Niu","year":"2022","unstructured":"Niu JJ, Chen DG, Li JH, Wang H (2022) A dynamic rule-based classification model via granular computing. Info Sci 584:325\u2013341","journal-title":"Info Sci"},{"key":"10499_CR22","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.ijar.2008.08.004","volume":"50","author":"YH Qian","year":"2009","unstructured":"Qian YH, Liang JY, Dang CY (2009) Knowledge structure, knowledge granulation and knowledge distance in a knowledge base. Int J Approx Reason 50:174\u2013188","journal-title":"Int J Approx Reason"},{"key":"10499_CR23","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1016\/j.artint.2010.04.018","volume":"174","author":"YH Qian","year":"2010","unstructured":"Qian YH, Liang JY, Pedrycz W, Dang CY (2010) Positive approximation: an accelerator for attribute reduction in rough set theory. Artif Intell 174:597\u2013618","journal-title":"Artif Intell"},{"key":"10499_CR24","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.ins.2016.11.024","volume":"382\u2013383","author":"YH Qian","year":"2017","unstructured":"Qian YH, Cheng HH, Wang JT, Liang JY, Pedrycz W, Dang CY (2017) Grouping granular structures in human granulation intelligence. Info Sci 382\u2013383:150\u2013169","journal-title":"Info Sci"},{"key":"10499_CR25","first-page":"06014","volume":"200","author":"XS Rao","year":"2020","unstructured":"Rao XS, Yang XB, Yang X, Chen XJ, Liu D, Qian YH (2020) Quickly calculating reduct: an attribute relationship based approach. Knowl Based Syst 200:06014","journal-title":"Knowl Based Syst"},{"key":"10499_CR26","doi-asserted-by":"crossref","first-page":"2106","DOI":"10.1016\/j.patcog.2009.12.011","volume":"43","author":"D San","year":"2010","unstructured":"San D, Zhang DQ (2010) Bagging constraint score for feature selection with pairwise constraint. Pattern Recog 43:2106\u20132118","journal-title":"Pattern Recog"},{"key":"10499_CR27","doi-asserted-by":"crossref","first-page":"3890","DOI":"10.1016\/j.patcog.2014.06.002","volume":"47","author":"WH Shu","year":"2014","unstructured":"Shu WH, Shen H (2014) Incremental feature selection based on rough set in dynamic incomplete data. Pattern Recog 47:3890\u20133906","journal-title":"Pattern Recog"},{"key":"10499_CR28","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1109\/TFUZZ.2020.2989098","volume":"29","author":"L Sun","year":"2021","unstructured":"Sun L, Wang LY, Ding WP, Qian YH, Xu JC (2021) Feature selection using fuzzy neighborhood entropy-based uncertainty measures for fuzzy neighborhood multigranulation rough sets. IEEE Trans Fuzz Syst 29:19\u201333","journal-title":"IEEE Trans Fuzz Syst"},{"key":"10499_CR29","first-page":"2986","volume":"29","author":"CZ Wang","year":"2018","unstructured":"Wang CZ, Hu QH, Wang XZ, Chen DG, Qian YH, Dong Z (2018) Feature selection based on neighborhood discrimination index. IEEE Trans Neural Netw Learn Syst 29:2986\u20132999","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10499_CR30","first-page":"1","volume":"99","author":"CZ Wang","year":"2019","unstructured":"Wang CZ, Huang Y, Shao MW, Hu QH (2019) Feature selection based on neighborhood self-information. IEEE Trans Cybern 99:1\u201312","journal-title":"IEEE Trans Cybern"},{"key":"10499_CR31","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.neucom.2019.01.029","volume":"335","author":"ZB Wu","year":"2019","unstructured":"Wu ZB, Mao KZ, Ng GW (2019) Enhanced feature fusion through irrelevant redundancy elimination in intra-class and extra-class discriminative correlation analysis. Neurocomputing 335:105\u2013118","journal-title":"Neurocomputing"},{"key":"10499_CR32","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.ins.2019.01.010","volume":"483","author":"SY Xia","year":"2019","unstructured":"Xia SY, Liu YS, Ding X, Wang GY, Yu H, Lu YG (2019) Granular ball computing classififiers for efficient, scalable and robust learning. Info Sci 483:136\u2013152","journal-title":"Info Sci"},{"key":"10499_CR33","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.knosys.2016.04.012","volume":"104","author":"SP Xu","year":"2016","unstructured":"Xu SP, Yang XB, Yu HL, Yu DJ, Yang JY, Tsang ECC (2016) Multi-label learning with label-specific feature reduction. Knowl Based Syst 104:52\u201361","journal-title":"Knowl Based Syst"},{"issue":"2","key":"10499_CR34","doi-asserted-by":"crossref","first-page":"117","DOI":"10.32604\/jcs.2021.017018","volume":"3","author":"Y Xue","year":"2021","unstructured":"Xue Y, Aouari A, Mansour RF, Su SB (2021) A hybrid algorithm based on PSO and GA for feature selection. J Cyber Secur 3(2):117\u2013124","journal-title":"J Cyber Secur"},{"key":"10499_CR35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.asoc.2018.05.013","volume":"70","author":"XB Yang","year":"2018","unstructured":"Yang XB, Yao YY (2018) Ensemble selector for attribute reduction. Appl Soft Comput 70:1\u201311","journal-title":"Appl Soft Comput"},{"key":"10499_CR36","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.knosys.2014.03.021","volume":"64","author":"XB Yang","year":"2014","unstructured":"Yang XB, Qi Y, Yu HL, Song XN, Yang JY (2014) Updating multigranulation rough approximations with increasing of granular structures. Knowl Based Syst 64:59\u201369","journal-title":"Knowl Based Syst"},{"key":"10499_CR37","doi-asserted-by":"crossref","first-page":"277","DOI":"10.2991\/ijcis.2017.10.1.19","volume":"10","author":"XB Yang","year":"2017","unstructured":"Yang XB, Xu SP, Dou HL, Song XN, Yu HL, Yang JY (2017) Multigranulation rough set: a multiset based strategy. Int J Comput Intell Syst 10:277\u2013292","journal-title":"Int J Comput Intell Syst"},{"key":"10499_CR38","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.ins.2019.02.048","volume":"486","author":"X Yang","year":"2019","unstructured":"Yang X, Li TR, Liu D, Fujita H (2019) A temporal-spatial composite sequential approach of three-way granular computing. Inform Sci 486:171\u2013189","journal-title":"Inform Sci"},{"key":"10499_CR39","first-page":"100","volume":"5150","author":"YY Yao","year":"2008","unstructured":"Yao YY, Zhang Y, Wang J (2008) On reduct construction algorithms. Trans Comput Sci 5150:100\u2013117","journal-title":"Trans Comput Sci"},{"key":"10499_CR40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.patcog.2016.02.013","volume":"56","author":"X Zhang","year":"2016","unstructured":"Zhang X, Mei CL, Chen DG, Li JH (2016) Feature selection in mixed data: a method using a novel fuzzy rough set-based information entropy. Pattern Recog 56:1\u201315","journal-title":"Pattern Recog"},{"key":"10499_CR41","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.ins.2018.12.074","volume":"481","author":"P Zhou","year":"2019","unstructured":"Zhou P, Hua XG, Li PP, Wu XD (2019) Online streaming feature selection using adapted neighborhood rough set. Info Sci 481:258\u2013279","journal-title":"Info Sci"},{"key":"10499_CR42","doi-asserted-by":"crossref","first-page":"107375","DOI":"10.1016\/j.patcog.2020.107375","volume":"105","author":"P Zhou","year":"2020","unstructured":"Zhou P, Du L, Li XJ, Shen YD, Qian YH (2020) Unsupervised feature selection with adaptive multiple graph learning. Pattern Recog 105:107375","journal-title":"Pattern Recog"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-023-10499-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-023-10499-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-023-10499-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T08:34:32Z","timestamp":1692606872000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-023-10499-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,14]]},"references-count":42,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["10499"],"URL":"https:\/\/doi.org\/10.1007\/s10462-023-10499-z","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"type":"print","value":"0269-2821"},{"type":"electronic","value":"1573-7462"}],"subject":[],"published":{"date-parts":[[2023,5,14]]},"assertion":[{"value":"14 May 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interest"}}]}}