{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T17:57:09Z","timestamp":1732039029147},"reference-count":35,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902068"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Research and Development Project of Anhui Province","award":["KJ2019ZD44"]},{"name":"Major Special Projects of Anhui Province","award":["201903A06020026"]},{"DOI":"10.13039\/501100003995","name":"Anhui Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["1908085MF211"],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1016\/j.eswa.2020.113352","type":"journal-article","created":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T00:45:41Z","timestamp":1583282741000},"page":"113352","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":33,"special_numbering":"C","title":["Locality adaptive preserving projections for linear dimensionality reduction"],"prefix":"10.1016","volume":"151","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-6150-8068","authenticated-orcid":false,"given":"Aiguo","family":"Wang","sequence":"first","affiliation":[]},{"given":"Shenghui","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Jinjun","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3922-299X","authenticated-orcid":false,"given":"Jing","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4776-5292","authenticated-orcid":false,"given":"Li","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Guilin","family":"Chen","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.eswa.2020.113352_bib0001","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1038\/nbt.4314","article-title":"Dimensionality reduction for visualizing single-cell data using UMAP","volume":"37","author":"Becht","year":"2019","journal-title":"Nature Biotechnology"},{"issue":"7","key":"10.1016\/j.eswa.2020.113352_bib0002","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/34.598228","article-title":"Eigenfaces vs. fisherfaces: Recognition using class specific linear projection","volume":"19","author":"Belhumeur","year":"1997","journal-title":"IEEE Transactions on Pattern Analysis on Machine Intelligence"},{"key":"10.1016\/j.eswa.2020.113352_bib0003","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.eswa.2018.08.047","article-title":"Enhancement of robustness of face recognition system through reduced gaussianity in Log-ICA","volume":"116","author":"Bhowmik","year":"2019","journal-title":"Expert Systems with Applications"},{"issue":"11","key":"10.1016\/j.eswa.2020.113352_bib0004","doi-asserted-by":"crossref","first-page":"3608","DOI":"10.1109\/TIP.2006.881945","article-title":"Orthogonal laplacianfaces for face recognition","volume":"15","author":"Cai","year":"2006","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2020.113352_bib0005","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.patrec.2019.05.009","article-title":"Similarity preservation in dimensionality reduction using a kernel-based cost function","volume":"125","author":"Garcia-Vega","year":"2019","journal-title":"Pattern Recognition Letters"},{"key":"10.1016\/j.eswa.2020.113352_bib0006","series-title":"Proceedings of IEEE international conference on computer vision (ICCV)","first-page":"1208","article-title":"Neighborhood preserving embedding","author":"He","year":"2005"},{"key":"10.1016\/j.eswa.2020.113352_bib0007","series-title":"Proceedings of advances in neural information processing systems (NeurIPS)","first-page":"153","article-title":"Locality preserving projections","author":"He","year":"2004"},{"issue":"3","key":"10.1016\/j.eswa.2020.113352_bib0008","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/TPAMI.2005.55","article-title":"Face recognition using Laplacianfaces","volume":"27","author":"He","year":"2005","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"5786","key":"10.1016\/j.eswa.2020.113352_bib0009","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","article-title":"Reducing the dimensionality of data with neural networks","volume":"313","author":"Hinton","year":"2006","journal-title":"Science (New York, N.Y.)"},{"key":"10.1016\/j.eswa.2020.113352_bib0010","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.eswa.2016.09.014","article-title":"GMMs similarity measure based on LPP-like projection of the parameter space","volume":"66","author":"Krstanovi\u0107","year":"2016","journal-title":"Expert Systems with Applications"},{"issue":"5","key":"10.1016\/j.eswa.2020.113352_bib0011","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1109\/TPAMI.2005.92","article-title":"Acquiring linear subspaces for face recognition under variable lighting","volume":"27","author":"Lee","year":"2005","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"2","key":"10.1016\/j.eswa.2020.113352_bib0012","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1109\/34.908974","article-title":"PCA versus LDA","volume":"23","author":"Mart\u00ednez","year":"2001","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"9","key":"10.1016\/j.eswa.2020.113352_bib0013","doi-asserted-by":"crossref","first-page":"2779","DOI":"10.1109\/TNNLS.2018.2886317","article-title":"Simultaneously learning neighborship and projection matrix for supervised dimensionality reduction","volume":"30","author":"Pang","year":"2019","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"8","key":"10.1016\/j.eswa.2020.113352_bib0014","first-page":"3429","article-title":"Dimensionality reduction using similarity-induced embeddings","volume":"29","author":"Passalis","year":"2017","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"1","key":"10.1016\/j.eswa.2020.113352_bib0015","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.patcog.2009.05.005","article-title":"Sparsity preserving projections with applications to face recognition","volume":"43","author":"Qiao","year":"2010","journal-title":"Pattern Recognition"},{"issue":"5500","key":"10.1016\/j.eswa.2020.113352_bib0016","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","article-title":"Nonlinear dimensionality reduction by locally linear embedding","volume":"290","author":"Roweis","year":"2000","journal-title":"Science (New York, N.Y.)"},{"key":"10.1016\/j.eswa.2020.113352_bib0017","series-title":"Proceeding of IEEE workshop on applications of computer vision (ACV)","first-page":"138","article-title":"Parameterisation of a stochastic model for human face identification","author":"Samaria","year":"1994"},{"issue":"5","key":"10.1016\/j.eswa.2020.113352_bib0018","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1162\/089976698300017467","article-title":"Nonlinear component analysis as a kernel eigenvalue problem","volume":"10","author":"Sch\u00f6lkopf","year":"1998","journal-title":"Neural Computation"},{"issue":"9","key":"10.1016\/j.eswa.2020.113352_bib0019","doi-asserted-by":"crossref","first-page":"2789","DOI":"10.1016\/j.patcog.2008.01.001","article-title":"A unified framework for semi-supervised dimensionality reduction","volume":"41","author":"Song","year":"2008","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2020.113352_bib0020","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.eswa.2017.09.009","article-title":"Dimension reduction in mean-variance portfolio optimization","volume":"92","author":"Tayal\u0131","year":"2018","journal-title":"Expert Systems with Applications"},{"issue":"5500","key":"10.1016\/j.eswa.2020.113352_bib0021","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","article-title":"A global geometric framework for nonlinear dimensionality reduction","volume":"290","author":"Tenenbaum","year":"2000","journal-title":"Science (New York, N.Y.)"},{"key":"10.1016\/j.eswa.2020.113352_bib0022","series-title":"Proceedings of advances neural information processing systems (NeurIPS)","first-page":"841","article-title":"Automatic alignment of hidden representations","author":"The","year":"2002"},{"key":"10.1016\/j.eswa.2020.113352_bib0023","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.eswa.2020.113352_bib0024","unstructured":"van der Maaten, L., Postma, E., & Herik, H. (2009). Dimensionality reduction: A comparative review. URLhttp:\/\/lvdmaaten.github.io\/publications\/papers\/TR_Dimensionality_Reduction_Review_2009.pdf"},{"issue":"11","key":"10.1016\/j.eswa.2020.113352_bib0025","doi-asserted-by":"crossref","first-page":"4566","DOI":"10.1109\/JSEN.2016.2545708","article-title":"A comparative study on human activity recognition using inertial sensors in a smartphone","volume":"16","author":"Wang","year":"2016","journal-title":"IEEE Sensors Journal"},{"key":"10.1016\/j.eswa.2020.113352_bib0026","series-title":"Proceedings of advances in neural information processing systems (NeurIPS)","first-page":"1473","article-title":"Distance metric learning for large margin nearest neighbor classification","author":"Weinberger","year":"2006"},{"key":"10.1016\/j.eswa.2020.113352_bib0027","series-title":"Proceedings of the twenty-first international conference on machine learning (ICML-04)","first-page":"106","article-title":"Learning a kernel matrix for nonlinear dimensionality reduction","author":"Weinberger","year":"2004"},{"issue":"1","key":"10.1016\/j.eswa.2020.113352_bib0028","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/TPAMI.2007.250598","article-title":"Graph embedding and extensions: A general framework for dimensionality reduction","volume":"29","author":"Yan","year":"2007","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"16\u201318","key":"10.1016\/j.eswa.2020.113352_bib0029","doi-asserted-by":"crossref","first-page":"3644","DOI":"10.1016\/j.neucom.2008.03.009","article-title":"Null space discriminant locality preserving projections for face recognition","volume":"71","author":"Yang","year":"2008","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2020.113352_bib0030","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.neucom.2011.10.021","article-title":"Fast neighborhood component analysis","volume":"83","author":"Yang","year":"2012","journal-title":"Neurocomputing"},{"issue":"3","key":"10.1016\/j.eswa.2020.113352_bib0031","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.imavis.2005.11.006","article-title":"Face recognition using discriminant locality preserving projections","volume":"24","author":"Yu","year":"2006","journal-title":"Image and Vision Computing"},{"key":"10.1016\/j.eswa.2020.113352_bib0032","doi-asserted-by":"crossref","first-page":"6833","DOI":"10.1109\/ACCESS.2017.2697408","article-title":"Non-linear dimensionality reduction and Gaussian process-based classification method for smoke detection","volume":"5","author":"Yuan","year":"2017","journal-title":"IEEE access : practical innovations, open solutions"},{"key":"10.1016\/j.eswa.2020.113352_bib0033","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.patcog.2018.05.021","article-title":"Auto-weighted 2-dimensional maximum margin criterion","volume":"83","author":"Zhang","year":"2018","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2020.113352_bib0034","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.neucom.2018.06.045","article-title":"Adaptive neighborhood MinMax projections","volume":"313","author":"Zhao","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2020.113352_bib0035","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.eswa.2016.09.027","article-title":"Forecasting daily stock market return using dimensionality reduction","volume":"67","author":"Zhong","year":"2017","journal-title":"Expert Systems with Applications"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417420301779?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417420301779?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2020,4,28]],"date-time":"2020-04-28T02:12:40Z","timestamp":1588039960000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417420301779"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":35,"alternative-id":["S0957417420301779"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2020.113352","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2020,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Locality adaptive preserving projections for linear dimensionality reduction","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2020.113352","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"113352"}}