{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T07:35:34Z","timestamp":1771572934824,"version":"3.50.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,6,28]],"date-time":"2023-06-28T00:00:00Z","timestamp":1687910400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,28]],"date-time":"2023-06-28T00:00:00Z","timestamp":1687910400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s11042-023-15821-z","type":"journal-article","created":{"date-parts":[[2023,6,28]],"date-time":"2023-06-28T07:02:21Z","timestamp":1687935741000},"page":"11247-11260","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Feature subset selection algorithm based on symmetric uncertainty and interaction factor"],"prefix":"10.1007","volume":"83","author":[{"given":"Xiangyuan","family":"Gu","sequence":"first","affiliation":[]},{"given":"Jianguo","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Guoqiang","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Kun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jiaxing","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,28]]},"reference":[{"key":"15821_CR1","first-page":"1","volume":"10008","author":"V Blondel","year":"2008","unstructured":"Blondel V, Lambiotte JGR, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech: Theory Exp 10008:1\u201312","journal-title":"J Stat Mech: Theory Exp"},{"key":"15821_CR2","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.knosys.2015.05.014","volume":"86","author":"CV Bolon","year":"2015","unstructured":"Bolon CV, Sanchez MN, Alonso BA (2015) Recent advances and emerging challenges of feature selection in the context of big data. Knowl-Based Syst 86:33\u201345","journal-title":"Knowl-Based Syst"},{"key":"15821_CR3","first-page":"27","volume":"13","author":"G Brown","year":"2012","unstructured":"Brown G, Pocock A, Zhao MJ, Lujan M (2012) Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection. J Mach Learn Res 13:27\u201366","journal-title":"J Mach Learn Res"},{"key":"15821_CR4","doi-asserted-by":"crossref","unstructured":"Deep PK (2022) A random walk Grey wolf optimizer based on dispersion factor for feature selection on chronic disease prediction. Expert Syst Appl 206","DOI":"10.1016\/j.eswa.2022.117864"},{"key":"15821_CR5","volume-title":"UCI machine learning repository","author":"D Dua","year":"2019","unstructured":"Dua D, Graff C (2019) UCI machine learning repository. University of California, Irvine, School of Information and Computer Sciences"},{"key":"15821_CR6","doi-asserted-by":"crossref","unstructured":"Ershadi MM, Seifi A (2022) Applications of dynamic feature selection and clustering methods to medical diagnosis. Appl Soft Comput 126","DOI":"10.1016\/j.asoc.2022.109293"},{"key":"15821_CR7","unstructured":"Fayyad UM, Irani KB (1993) Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. In: Proceedings of International Joint Conference on Artificial Intelligence, pp 1022-1027"},{"key":"15821_CR8","first-page":"1531","volume":"5","author":"F Fleuret","year":"2004","unstructured":"Fleuret F (2004) Fast binary feature selection with conditional mutual information. J Mach Learn Res 5:1531\u20131555","journal-title":"J Mach Learn Res"},{"key":"15821_CR9","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1016\/j.patcog.2018.02.020","volume":"79","author":"WF Gao","year":"2018","unstructured":"Gao WF, Hu L, Zhang P (2018) Class-specific mutual information variation for feature selection. Pattern Recogn 79:328\u2013339","journal-title":"Pattern Recogn"},{"key":"15821_CR10","doi-asserted-by":"crossref","unstructured":"Grag M (2022) UBIS: Unigram Bigram Importance Score for Feature Selection from Short Text. Expert Syst Appl 195","DOI":"10.1016\/j.eswa.2022.116563"},{"issue":"14","key":"15821_CR11","doi-asserted-by":"publisher","first-page":"19681","DOI":"10.1007\/s11042-019-7285-1","volume":"78","author":"XY Gu","year":"2019","unstructured":"Gu XY, Guo JC (2019) A study on Subtractive Pixel Adjacency Matrix features. Multimedia Tools and Applications 78(14):19681\u201319695","journal-title":"Multimedia Tools and Applications"},{"issue":"13","key":"15821_CR12","doi-asserted-by":"publisher","first-page":"8785","DOI":"10.1007\/s00500-021-05800-7","volume":"25","author":"XY Gu","year":"2021","unstructured":"Gu XY, Guo JC (2021) A feature subset selection algorithm based on equal interval division and three-way interaction information. Soft Comput 25(13):8785\u20138795","journal-title":"Soft Comput"},{"issue":"1","key":"15821_CR13","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/s00500-019-03910-x","volume":"24","author":"XY Gu","year":"2020","unstructured":"Gu XY, Guo JC, Wei HW, He YH (2020) Spatial-domain steganalytic feature selection based on three-way interaction information and KS test. Soft Comput 24(1):333\u2013340","journal-title":"Soft Comput"},{"issue":"2","key":"15821_CR14","doi-asserted-by":"publisher","first-page":"1237","DOI":"10.1007\/s11063-019-10144-3","volume":"51","author":"XY Gu","year":"2020","unstructured":"Gu XY, Guo JC, Xiao LJ, Ming T, Li CY (2020) A Feature Selection Algorithm Based on Equal Interval Division and Minimal-Redundancy-Maximal-Relevance. Neural Process Lett 51(2):1237\u20131263","journal-title":"Neural Process Lett"},{"issue":"2","key":"15821_CR15","first-page":"214","volume":"54","author":"XY Gu","year":"2021","unstructured":"Gu XY, Guo JC, Li CY, Xiao LJ (2021) Feature subset selection algorithm based on symmetric uncertainty and three-way interaction information. Journal of Tianjin University (Science and Technology) 54(2):214\u2013220","journal-title":"Journal of Tianjin University (Science and Technology)"},{"issue":"4","key":"15821_CR16","doi-asserted-by":"publisher","first-page":"2672","DOI":"10.1007\/s10489-020-01936-5","volume":"51","author":"XY Gu","year":"2021","unstructured":"Gu XY, Guo JC, Li CY, Xiao LJ (2021) A feature selection algorithm based on redundancy analysis and interaction weight. Appl Intell 51(4):2672\u20132686","journal-title":"Appl Intell"},{"key":"15821_CR17","doi-asserted-by":"publisher","first-page":"1436","DOI":"10.1007\/s10489-021-02412-4","volume":"52","author":"XY Gu","year":"2022","unstructured":"Gu XY, Guo JC, Xiao LJ, Li CY (2022) Conditional mutual information-based feature selection algorithm for maximal relevance minimal redundancy. Appl Intell 52:1436\u20131447","journal-title":"Appl Intell"},{"issue":"3","key":"15821_CR18","doi-asserted-by":"publisher","first-page":"2079","DOI":"10.1007\/s11063-021-10720-6","volume":"54","author":"XY Gu","year":"2022","unstructured":"Gu XY, Guo JC, Ming T, Xiao LJ, Li CY (2022) A Feature Selection Algorithm Based on Equal Interval Division and Conditional Mutual Information. Neural Process Lett 54(3):2079\u20132105","journal-title":"Neural Process Lett"},{"issue":"1","key":"15821_CR19","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The WEKA data mining software: an update. ACM SIGKDD Explorations Newsl 11(1):10\u201318","journal-title":"ACM SIGKDD Explorations Newsl"},{"issue":"1","key":"15821_CR20","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1109\/72.977291","volume":"13","author":"N Kwak","year":"2002","unstructured":"Kwak N, Choi CH (2002) Input feature selection for classification problems. IEEE Trans Neural Networks 13(1):143\u2013159","journal-title":"IEEE Trans Neural Networks"},{"key":"15821_CR21","doi-asserted-by":"crossref","unstructured":"Li JD, Cheng KW, Wang SH, Morstatter F, Trevino RP, Tang JL, Liu H (2018) Feature Selection: A Data Perspective. ACM Comput Surv 50(6)","DOI":"10.1145\/3136625"},{"key":"15821_CR22","doi-asserted-by":"crossref","unstructured":"Maldonado J, Riff MC, Neveu B (2022) A review of recent approaches on wrapper feature selection for intrusion detection. Expert Syst Appl 198","DOI":"10.1016\/j.eswa.2022.116822"},{"key":"15821_CR23","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.knosys.2015.04.007","volume":"84","author":"P Moradi","year":"2015","unstructured":"Moradi P, Rostami M (2015) Integration of graph clustering with ant colony optimization for feature selection. Knowl-Based Syst 84:144\u2013161","journal-title":"Knowl-Based Syst"},{"issue":"8","key":"15821_CR24","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"HC Peng","year":"2005","unstructured":"Peng HC, Long FH, Ding C (2005) Feature selection based on mutual information: Criteria of max-dependency, max-relevance and min-redundancy. IEEE Trans Pattern Anal Mach Intell 27(8):1226\u20131238","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"15821_CR25","doi-asserted-by":"crossref","unstructured":"Piho L, Tjahjadi T (2020) A Mutual Information Based Adaptive Windowing of Informative EEG for Emotion Recognition. IEEE Trans Affect Comput 11(4)","DOI":"10.1109\/TAFFC.2018.2840973"},{"issue":"1","key":"15821_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TKDE.2011.181","volume":"25","author":"QB Song","year":"2013","unstructured":"Song QB, Ni JJ, Wang GT (2013) A fast clustering-based feature subset selection algorithm for high-dimensional data. IEEE Trans Knowl Data Eng 25(1):1\u201314","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"15821_CR27","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.patrec.2021.03.034","volume":"147","author":"K Thirumoorthy","year":"2021","unstructured":"Thirumoorthy K, Muneeswaran K (2021) Feature selection using hybrid poor and rich optimization algorithm for text classification. Pattern Recogn Lett 147:63\u201370","journal-title":"Pattern Recogn Lett"},{"issue":"1","key":"15821_CR28","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1007\/s00521-013-1368-0","volume":"24","author":"JR Vergara","year":"2014","unstructured":"Vergara JR, Estevez PA (2014) A review of feature selection methods based on mutual information. Neural Comput Appl 24(1):175\u2013186","journal-title":"Neural Comput Appl"},{"issue":"3","key":"15821_CR29","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/s10115-012-0487-8","volume":"34","author":"BC Veronica","year":"2013","unstructured":"Veronica BC, Noelia SM, Amparo AB (2013) A review of feature selection methods on synthetic data. Knowl Inf Syst 34(3):483\u2013519","journal-title":"Knowl Inf Syst"},{"key":"15821_CR30","doi-asserted-by":"crossref","unstructured":"Wang LX, Jiang SY, Jiang SY (2021) A feature selection method via analysis of relevance, redundancy, and interaction. Expert Syst Appl 183","DOI":"10.1016\/j.eswa.2021.115365"},{"key":"15821_CR31","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.ins.2015.02.031","volume":"307","author":"ZC Wang","year":"2015","unstructured":"Wang ZC, Li MQ, Li JZ (2015) A multi-objective evolutionary algorithm for feature selection based on mutual information with a new redundancy measure. Inf Sci 307:73\u201388","journal-title":"Inf Sci"},{"key":"15821_CR32","doi-asserted-by":"crossref","unstructured":"Yin KX, Xie AF, Zhai JR, Zhu JQ (2022) Dynamic interaction-based feature selection algorithm for maximal relevance minimal redundancy. Appl Intell","DOI":"10.1007\/s10489-022-03922-5"},{"key":"15821_CR33","first-page":"1205","volume":"5","author":"L Yu","year":"2004","unstructured":"Yu L, Liu H (2004) Efficient feature selection via analysis of relevance and redundancy. J Mach Learn Res 5:1205\u20131224","journal-title":"J Mach Learn Res"},{"issue":"2","key":"15821_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2976744","volume":"11","author":"K Yu","year":"2016","unstructured":"Yu K, Wu XD, Ding W, Pei J (2016) Scalable and accurate online feature selection for big data. ACM Trans Knowl Discov Data 11(2):1\u201339","journal-title":"ACM Trans Knowl Discov Data"},{"key":"15821_CR35","doi-asserted-by":"crossref","unstructured":"Yu K, Wu XD, Ding W, Pei J (2014) Towards scalable and accurate online feature selection for big data. In: Proceedings of International Conference on Data Mining, pp 660-669","DOI":"10.1109\/ICDM.2014.63"},{"key":"15821_CR36","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.knosys.2014.03.022","volume":"64","author":"YS Zhang","year":"2014","unstructured":"Zhang YS, Yang AR, Xiong C, Wang T, Zhang ZG (2014) Feature selection using data envelopment analysis. Knowl-Based Syst 64:70\u201380","journal-title":"Knowl-Based Syst"},{"issue":"4","key":"15821_CR37","first-page":"86","volume":"41","author":"L Zhang","year":"2018","unstructured":"Zhang L, Yuan YY, Wang C (2018) FCBF Feature Selection Algorithm Based on Maximum Information Coefficient. Journal of Beijing University of Posts and Telecommunications 41(4):86\u201390","journal-title":"Journal of Beijing University of Posts and Telecommunications"},{"issue":"2","key":"15821_CR38","doi-asserted-by":"publisher","first-page":"207","DOI":"10.3233\/IDA-2009-0364","volume":"13","author":"Z Zhao","year":"2009","unstructured":"Zhao Z, Liu H (2009) Searching for interacting features in subset selection. Intelligent Data Analysis 13(2):207\u2013228","journal-title":"Intelligent Data Analysis"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15821-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-15821-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15821-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T09:46:54Z","timestamp":1704880014000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-15821-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,28]]},"references-count":38,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["15821"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-15821-z","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,28]]},"assertion":[{"value":"15 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 April 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 May 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 June 2023","order":4,"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 conflict of interest and this research has not received any external funding.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests\/Competing interests"}}]}}