{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T04:30:57Z","timestamp":1784867457675,"version":"3.55.0"},"reference-count":46,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T00:00:00Z","timestamp":1629331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001843","name":"Science and Engineering Research Board","doi-asserted-by":"crossref","award":["ECR\/2017\/000053"],"award-info":[{"award-number":["ECR\/2017\/000053"]}],"id":[{"id":"10.13039\/501100001843","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Department of Science and Technology, INDIA","award":["SB\/S2\/RJN-001\/2016"],"award-info":[{"award-number":["SB\/S2\/RJN-001\/2016"]}]},{"name":"Council of Scientific & Industrial Research (CSIR), New Delhi, INDIA","award":["22(0751)\/17\/EMR-II"],"award-info":[{"award-number":["22(0751)\/17\/EMR-II"]}]},{"DOI":"10.13039\/100014041","name":"Alzheimer\u2019s Disease Neuroimaging Initiative","doi-asserted-by":"crossref","award":["U01 AG024904"],"award-info":[{"award-number":["U01 AG024904"]}],"id":[{"id":"10.13039\/100014041","id-type":"DOI","asserted-by":"crossref"}]},{"name":"DOD ADNI","award":["W81XWH-12-2-0012"],"award-info":[{"award-number":["W81XWH-12-2-0012"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Internet Technol."],"published-print":{"date-parts":[[2021,8,31]]},"abstract":"<jats:p>Universum-based support vector machine incorporates prior information about the distribution of data in training of the classifier. This leads to better generalization performance but with increased computation cost. Various twin hyperplane-based models are proposed to reduce the computation cost of universum-based algorithms. In this work, we present an efficient angle-based universum least squares twin support vector machine (AULSTSVM) for classification. This is a novel approach of incorporating universum in the formulation of least squares-based twin SVM model. First, the proposed AULSTSVM constructs a universum hyperplane, which is proximal to universum data points. Then, the classifying hyperplane is constructed by minimizing the angle with the universum hyperplane. This gives prior information about data distribution to the classifier. In addition to the quadratic loss, we introduce linear loss in the optimization problem of the proposed AULSTSVM, which leads to lesser computation cost of the model. Numerical experiments are performed on several benchmark synthetic, real-world, and large-scale datasets. The results show that proposed AULSTSVM performs better than existing algorithms w.r.t. generalization performance as well as computation time. Moreover, an application to Alzheimer\u2019s disease is presented, where AULSTSVM obtains accuracy of 95% for classification of healthy and Alzheimers subjects. The results imply that the proposed AULSTSVM is a better alternative for classification of large-scale datasets and biomedical applications.<\/jats:p>","DOI":"10.1145\/3387131","type":"journal-article","created":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T12:39:34Z","timestamp":1594125574000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":30,"title":["An Efficient Angle-based Universum Least Squares Twin Support Vector Machine for Classification"],"prefix":"10.1145","volume":"21","author":[{"given":"B.","family":"Richhariya","sequence":"first","affiliation":[{"name":"Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Tanveer","sequence":"additional","affiliation":[{"name":"Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Alzheimer\u2019s Disease Neuroimaging Initiative Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, India Program","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,8,19]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"255","article-title":"Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework.J","volume":"17","author":"Alcal\u00e1-Fdez Jes\u00fas","year":"2011","journal-title":"Multiple-Valued Logic Soft Comput."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.08.034"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2017.02.011"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/2981562.2981734"},{"key":"e_1_2_1_5_1","first-page":"1","article-title":"Recognition of schizophrenia with regularized support vector machine and sequential region of interest selection using structural magnetic resonance imaging. Sci","volume":"8","author":"Chin Rowena","year":"2018","journal-title":"Rep."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1022627411411"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/1248547.1248548"},{"key":"e_1_2_1_8_1","unstructured":"Dheeru Dua and Casey Graff. 2017. UCI Machine Learning Repository. Retrieved from http:\/\/archive.ics.uci.edu\/ml.  Dheeru Dua and Casey Graff. 2017. UCI Machine Learning Repository. Retrieved from http:\/\/archive.ics.uci.edu\/ml."},{"key":"e_1_2_1_9_1","volume-title":"Van Loan","author":"Golub Gene H.","year":"2012"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2914465"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.1068"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.04.038"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-017-2604-2"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.09.066"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2684-y"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00234-008-0463-x"},{"key":"e_1_2_1_17_1","volume-title":"NDC: Normally distributed clustered datasets. Computer Sciences Department","author":"Musicant D. R.","year":"1998"},{"key":"e_1_2_1_18_1","volume-title":"Report","author":"Patterson Christina","year":"2018"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2012.09.004"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.10.008"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.02.084"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2018.11.046"},{"key":"e_1_2_1_23_1","volume-title":"Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (SSCI\u201918)","author":"Richhariya B.","year":"2045"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.03.053"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107150"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2020.101903"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.06.014"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2014.10.011"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.11.028"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.05.025"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-014-0786-3"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-014-9278-8"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105617"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-015-0751-1"},{"key":"e_1_2_1_35_1","volume-title":"Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC\u201919)","author":"Tanveer M."},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3344998"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.04.032"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.02.022"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40745-014-0018-4"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103461"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.04.056"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143971"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.10.019"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1080\/00207721.2015.1110212"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-015-0736-0"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.01.031"}],"container-title":["ACM Transactions on Internet Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3387131","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3387131","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:33:26Z","timestamp":1750199606000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3387131"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,19]]},"references-count":46,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,8,31]]}},"alternative-id":["10.1145\/3387131"],"URL":"https:\/\/doi.org\/10.1145\/3387131","relation":{},"ISSN":["1533-5399","1557-6051"],"issn-type":[{"value":"1533-5399","type":"print"},{"value":"1557-6051","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,19]]},"assertion":[{"value":"2019-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-03-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-08-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}