{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T06:35:26Z","timestamp":1771655726452,"version":"3.50.1"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T00:00:00Z","timestamp":1597276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T00:00:00Z","timestamp":1597276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Front. Comput. Sci."],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s11704-019-9115-z","type":"journal-article","created":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T10:06:32Z","timestamp":1597313192000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Pointwise manifold regularization for semi-supervised learning"],"prefix":"10.1007","volume":"15","author":[{"given":"Yunyun","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiao","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yating","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Xue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,13]]},"reference":[{"issue":"3","key":"9115_CR1","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1007\/s10115-009-0209-z","volume":"24","author":"Z H Zhou","year":"2010","unstructured":"Zhou Z H, Li M. Semi-supervised learning by disagreement. Knowledge and Information Systems, 2010, 24(3): 415\u2013439","journal-title":"Knowledge and Information Systems"},{"issue":"1","key":"9115_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00196ED1V01Y200906AIM006","volume":"3","author":"X J Zhu","year":"2009","unstructured":"Zhu X J, Goldberg A B. Introduction to semi-supervised learning. Synthesis Lectures on Artificial Intelligence and Machine Learning, 2009, 3(1): 1\u2013130","journal-title":"Synthesis Lectures on Artificial Intelligence and Machine Learning"},{"key":"9115_CR3","unstructured":"Zhu X J. Semi-supervised learning literature survey. Technical Report, 2005"},{"key":"9115_CR4","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262033589.001.0001","volume-title":"Semi-supervised Learning","author":"O Chapelle","year":"2006","unstructured":"Chapelle O, Sch\u00f6lkopf B, Zien A. Semi-supervised Learning. Cambridge, MA: MIT Press, 2006"},{"issue":"11","key":"9115_CR5","doi-asserted-by":"publisher","first-page":"2000","DOI":"10.1109\/TPAMI.2008.235","volume":"31","author":"P K Mallapragada","year":"2008","unstructured":"Mallapragada P K, Jin R, Jain A K, Liu Y. Semiboost: boosting for semi-supervised learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 31(11): 2000\u20132014","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"9115_CR6","unstructured":"Joachims T. Transductive inference for text classification using support vector machines. In: Proceedings of the 16th Annual International Conference on Machine Learning. 1999, 200\u2013209"},{"issue":"1","key":"9115_CR7","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1080\/10556780108805809","volume":"15","author":"G Fung","year":"2001","unstructured":"Fung G, Mangasarian O L. Semi-supervised support vector machines for unlabeled data classification. Optimization Methods and Software, 2001, 15(1): 29\u201344","journal-title":"Optimization Methods and Software"},{"issue":"8","key":"9115_CR8","first-page":"1687","volume":"7","author":"R Collobert","year":"2006","unstructured":"Collobert R, Sinz F, Weston J, Bottou L. Large scale transductive SVMs. Journal of Machine Learning Research, 2006, 7(8): 1687\u20131712","journal-title":"Journal of Machine Learning Research"},{"key":"9115_CR9","doi-asserted-by":"crossref","unstructured":"Li Y F, Kwok J T, Zhou Z H. Semi-supervised learning using label mean. In: Proceedings of the 26th Annual International Conference on Machine Learning. 2009, 633\u2013640","DOI":"10.1145\/1553374.1553456"},{"key":"9115_CR10","doi-asserted-by":"crossref","first-page":"193","DOI":"10.7551\/mitpress\/6173.003.0016","volume-title":"Semi-supervised Learning","author":"Y Bengio","year":"2006","unstructured":"Bengio Y, Delalleau O, Roux N L. Label propagation and quadratic criterion. In: Chapelle O, Sch\u00f6lkopf B, Zien A, eds. Semi-supervised Learning. Cambridge, MA: MIT Press, 2006, 193\u2013216"},{"key":"9115_CR11","unstructured":"Zhu X J, Ghahramani Z. Learning from labeled and unlabeled data with label propagation. Technical Report, 2002"},{"key":"9115_CR12","unstructured":"Blum A, Chawla S. Learning from labeled and unlabeled data using graph mincuts. In: Proceedings of the 18th Annual International Conference on Machine Learning. 2001, 19\u201326"},{"issue":"11","key":"9115_CR13","first-page":"2399","volume":"7","author":"M Belkin","year":"2006","unstructured":"Belkin M, Niyogi P, Sindhwani V. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 2006, 7(11): 2399\u20132434","journal-title":"Journal of Machine Learning Research"},{"issue":"1","key":"9115_CR14","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TPAMI.2010.92","volume":"33","author":"K Chen","year":"2010","unstructured":"Chen K, Wang S H. Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 33(1): 129\u2013143","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"9115_CR15","first-page":"254","volume":"19","author":"X F He","year":"2009","unstructured":"He X F. Laplacian regularized D-optimal design for active learning and its application to image retrieval. IEEE Transactions on Image Processing, 2009, 19(1): 254\u2013263","journal-title":"IEEE Transactions on Image Processing"},{"key":"9115_CR16","doi-asserted-by":"crossref","unstructured":"Abernethy J, Chapelle O, Castillo C. Web spam identification through content and hyperlinks. In: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web. 2008, 41\u201344","DOI":"10.1145\/1451983.1451994"},{"key":"9115_CR17","unstructured":"Fang Y, Chang K C C, Lauw H W. Graph-based semi-supervised learning: realizing pointwise smoothness probabolistically. In: Proceedings of the 31st Annual International Conference on Machine Learning. 2014, 406\u2013414"},{"key":"9115_CR18","unstructured":"Singh A, Nowak R, Zhu J. Unlabeled data: now it helps, now it doesn\u2019t. In: Proceedings of Advances in Neural Information Processing Systems. 2009, 1513\u20131520"},{"key":"9115_CR19","unstructured":"Wasserman L, Lafferty J D. Statistical analysis of semi-supervised regression. In: Proceedings of Advances in Neural Information Processing Systems. 2008, 801\u2013808"},{"issue":"7","key":"9115_CR20","first-page":"1369","volume":"8","author":"P Rigollet","year":"2007","unstructured":"Rigollet P. Generlization error bounds in semi-supervised classification under the cluster assumption. Journal of Machine Learning Research, 2007, 8(7): 1369\u20131392","journal-title":"Journal of Machine Learning Research"},{"issue":"4","key":"9115_CR21","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1007\/s11704-017-6543-5","volume":"12","author":"H Wang","year":"2018","unstructured":"Wang H, Wang S B, Li Y F. Instance selection method for improving graph-based semi-supervised learning. Frontiers of Computer Science, 2018, 12(4): 725\u2013735","journal-title":"Frontiers of Computer Science"},{"key":"9115_CR22","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.eswa.2018.04.031","volume":"107","author":"H Gan","year":"2018","unstructured":"Gan H, Li Z, Wu W, Luo Z, Huang R. Safety-aware graph-based semi-supervised learning. Expert Systems with Applications, 2018, 107: 243\u2013254","journal-title":"Expert Systems with Applications"},{"key":"9115_CR23","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.patrec.2017.09.004","volume":"98","author":"Y Wang","year":"2017","unstructured":"Wang Y, Meng Y, Li Y, Chen S C, Fu Z Y, Xue H. Semi-supervised manifold regularization with adaptive graph construction. Pattern Recognition Letters, 2017, 98: 90\u201395","journal-title":"Pattern Recognition Letters"},{"key":"9115_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2015.09.017","volume":"45","author":"H T Gan","year":"2016","unstructured":"Gan H T, Luo Z Z, Sun Y, Xi X G, Sang N, Huang R. Towards designing risk-based safe laplacian regularized least squares. Expert Systems with Applicaions, 2016, 45: 1\u20137","journal-title":"Expert Systems with Applicaions"},{"key":"9115_CR25","unstructured":"Quang M H, Bazzani L, Murino V. A unifying framework for vector-valued manifold regularization and multi-view learning. In: Proceedings of the 30th Annual International Conference on Machine Learning. 2013, 100\u2013108"}],"container-title":["Frontiers of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-019-9115-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11704-019-9115-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-019-9115-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T18:21:06Z","timestamp":1696530066000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11704-019-9115-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,13]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["9115"],"URL":"https:\/\/doi.org\/10.1007\/s11704-019-9115-z","relation":{},"ISSN":["2095-2228","2095-2236"],"issn-type":[{"value":"2095-2228","type":"print"},{"value":"2095-2236","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,13]]},"assertion":[{"value":"3 April 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 September 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 August 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"151303"}}