{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T20:42:01Z","timestamp":1773520921998,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"13","license":[{"start":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T00:00:00Z","timestamp":1671494400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T00:00:00Z","timestamp":1671494400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Natural Science Foundation of Chongqing, China","award":["cstc2021jcyj-msxmX0066"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0066"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22274134"],"award-info":[{"award-number":["22274134"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1007\/s10489-022-04385-4","type":"journal-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T08:02:40Z","timestamp":1671523360000},"page":"16961-16972","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Multi-view co-clustering with multi-similarity"],"prefix":"10.1007","volume":"53","author":[{"given":"Ling","family":"Zhao","sequence":"first","affiliation":[]},{"given":"Yunpeng","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Shanxiong","family":"Chen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4353-1621","authenticated-orcid":false,"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,20]]},"reference":[{"key":"4385_CR1","doi-asserted-by":"publisher","DOI":"10.1002\/9781118649480","volume-title":"Co-clustering: models, algorithms and applications","author":"G Govaert","year":"2013","unstructured":"Govaert G, Nadif M (2013) Co-clustering: models, algorithms and applications. Wiley, London"},{"key":"4385_CR2","doi-asserted-by":"crossref","unstructured":"Chen W, Wang H, Long Z, Li T (2022) Fast flexible bipartite graph model for co-clustering. IEEE Transactions on Knowledge and Data Engineering","DOI":"10.1109\/TKDE.2022.3194275"},{"key":"4385_CR3","doi-asserted-by":"crossref","unstructured":"Dhillon IS (2001) Co-clustering documents and words using bipartite spectral graph partitioning. In: Proceedings of the Seventh ACM SIGKDD international conference on knowledge discovery and data mining, pp 269\u2013274","DOI":"10.1145\/502512.502550"},{"key":"4385_CR4","doi-asserted-by":"crossref","unstructured":"Dhillon IS, Mallela S, Modha DS (2003) Information-theoretic co-clustering. In: Proceedings of the ninth ACM SIGKDD international conference on knowledge discovery and data mining, pp 89\u201398","DOI":"10.1145\/956750.956764"},{"key":"4385_CR5","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.knosys.2015.02.016","volume":"82","author":"ALV Pereira","year":"2015","unstructured":"Pereira ALV, Hruschka ER (2015) Simultaneous co-clustering and learning to address the cold start problem in recommender systems. Knowl-Based Syst 82:11\u201319","journal-title":"Knowl-Based Syst"},{"key":"4385_CR6","doi-asserted-by":"crossref","unstructured":"Long B, Zhang Z, Yu PS (2005) Co-clustering by block value decomposition. In: Proceedings of the eleventh ACM SIGKDD international conference on knowledge discovery in data mining, pp 635\u2013640","DOI":"10.1145\/1081870.1081949"},{"key":"4385_CR7","doi-asserted-by":"crossref","unstructured":"Fraj M, Ben Hajkacem MA, Essoussi N (2019) Ensemble method for multi-view text clustering. In: International conference on computational collective intelligence. Springer, pp 219\u2013231","DOI":"10.1007\/978-3-030-28377-3_18"},{"issue":"4","key":"4385_CR8","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1007\/s00521-011-0647-x","volume":"21","author":"T-X Wu","year":"2012","unstructured":"Wu T-X, Lian X-C, Lu B-L (2012) Multi-view gender classification using symmetry of facial images. Neural Comput Appl 21(4):661\u2013669","journal-title":"Neural Comput Appl"},{"key":"4385_CR9","doi-asserted-by":"crossref","unstructured":"Xu Z, King I, Lyu MR (2007) Web page classification with heterogeneous data fusion. In: Proceedings of the 16th international conference on World Wide Web, pp 1171\u20131172","DOI":"10.1145\/1242572.1242750"},{"key":"4385_CR10","doi-asserted-by":"crossref","unstructured":"Gao J, Wang X, Wang Y, Xie X (2019) Explainable recommendation through attentive multi-view learning. In: Proceedings of the AAAI conference on artificial intelligence, vol 33, pp 3622\u2013 3629","DOI":"10.1609\/aaai.v33i01.33013622"},{"key":"4385_CR11","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.knosys.2019.03.023","volume":"175","author":"Q Xiao","year":"2019","unstructured":"Xiao Q, Dai J, Luo J, Fujita H (2019) Multi-view manifold regularized learning-based method for prioritizing candidate disease mirnas. Knowl-Based Syst 175:118\u2013129","journal-title":"Knowl-Based Syst"},{"key":"4385_CR12","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.neucom.2020.02.104","volume":"402","author":"L Fu","year":"2020","unstructured":"Fu L, Lin P, Vasilakos AV, Wang S (2020) An overview of recent multi-view clustering. Neurocomputing 402:148\u2013161","journal-title":"Neurocomputing"},{"key":"4385_CR13","unstructured":"Kumar A, Daum\u00e9 H (2011) A co-training approach for multi-view spectral clustering. In: Proceedings of the 28th international conference on machine learning (ICML-11), pp 393\u2013400"},{"key":"4385_CR14","first-page":"1413","volume":"24","author":"A Kumar","year":"2011","unstructured":"Kumar A, Rai P, Daume H (2011) Co-regularized multi-view spectral clustering. Adv Neural Inf Process Syst 24:1413\u20131421","journal-title":"Adv Neural Inf Process Syst"},{"key":"4385_CR15","doi-asserted-by":"crossref","unstructured":"Liu J, Cao F, Gao X-Z, Yu L, Liang J (2020) A cluster-weighted kernel k-means method for multi-view clustering. In: Proceedings of the Aaai conference on artificial intelligence, vol 34, pp 4860\u20134867","DOI":"10.1609\/aaai.v34i04.5922"},{"key":"4385_CR16","doi-asserted-by":"publisher","first-page":"107015","DOI":"10.1016\/j.patcog.2019.107015","volume":"97","author":"S Huang","year":"2020","unstructured":"Huang S, Kang Z, Xu Z (2020) Auto-weighted multi-view clustering via deep matrix decomposition. Pattern Recogn 97:107015","journal-title":"Pattern Recogn"},{"key":"4385_CR17","unstructured":"Nie F, Li J, Li X et al (2016) Parameter-free auto-weighted multiple graph learning: a framework for multiview clustering and semi-supervised classification. In: IJCAI, pp 1881\u20131887"},{"key":"4385_CR18","doi-asserted-by":"publisher","first-page":"105895","DOI":"10.1016\/j.cmpb.2020.105895","volume":"199","author":"X Zhang","year":"2021","unstructured":"Zhang X, Yang Y, Li T, Zhang Y, Wang H, Fujita H (2021) Cmc: a consensus multi-view clustering model for predicting alzheimer\u2019s disease progression. Comput Methods Prog Biomed 199:105895","journal-title":"Comput Methods Prog Biomed"},{"key":"4385_CR19","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.ins.2019.09.079","volume":"512","author":"S Huang","year":"2020","unstructured":"Huang S, Xu Z, Tsang IW, Kang Z (2020) Auto-weighted multi-view co-clustering with bipartite graphs. Inf Sci 512:18\u201330","journal-title":"Inf Sci"},{"key":"4385_CR20","doi-asserted-by":"crossref","unstructured":"Xu P, Deng Z, Choi K. -S., Cao L, Wang S (2019) Multi-view information-theoretic co-clustering for co-occurrence data. In: Proceedings of the AAAI conference on artificial intelligence, vol 33, pp 379\u2013386","DOI":"10.1609\/aaai.v33i01.3301379"},{"key":"4385_CR21","doi-asserted-by":"publisher","first-page":"107207","DOI":"10.1016\/j.patcog.2020.107207","volume":"102","author":"F Nie","year":"2020","unstructured":"Nie F, Shi S, Li X (2020) Auto-weighted multi-view co-clustering via fast matrix factorization. Pattern Recogn 102:107207","journal-title":"Pattern Recogn"},{"key":"4385_CR22","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.knosys.2015.03.027","volume":"84","author":"S Huang","year":"2015","unstructured":"Huang S, Wang H, Li D, Yang Y, Li T (2015) Spectral co-clustering ensemble. Knowl-Based Syst 84:46\u201355","journal-title":"Knowl-Based Syst"},{"issue":"99","key":"4385_CR23","first-page":"1","volume":"PP","author":"X Yu","year":"2019","unstructured":"Yu X, Yu G, Wang J, Domeniconi C (2019) Co-clustering ensembles based on multiple relevance measures. IEEE Trans Knowl Data Eng PP(99):1\u20131","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"4","key":"4385_CR24","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1007\/s11222-007-9033-z","volume":"17","author":"U Von Luxburg","year":"2007","unstructured":"Von Luxburg U (2007) A tutorial on spectral clustering. Statistics and computing 17(4):395\u2013416","journal-title":"Statistics and computing"},{"key":"4385_CR25","doi-asserted-by":"crossref","unstructured":"Tzortzis G, Likas A (2012) Kernel-based weighted multi-view clustering. In: 2012 IEEE 12th international conference on data mining. IEEE, pp 675\u2013684","DOI":"10.1109\/ICDM.2012.43"},{"issue":"1","key":"4385_CR26","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1007\/s10489-021-02405-3","volume":"52","author":"SF Hussain","year":"2022","unstructured":"Hussain SF, Khan K, Jillani R (2022) Weighted multi-view co-clustering (wmvcc) for sparse data. Appl Intell 52(1):398\u2013416","journal-title":"Appl Intell"},{"issue":"4","key":"4385_CR27","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1101\/gr.648603","volume":"13","author":"Y Kluger","year":"2003","unstructured":"Kluger Y, Basri R, Chang JT, Gerstein M (2003) Spectral biclustering of microarray data: coclustering genes and conditions. Genome Res 13(4):703\u2013716","journal-title":"Genome Res"},{"key":"4385_CR28","doi-asserted-by":"crossref","unstructured":"Kawale J, Boley D (2013) Constrained spectral clustering using l1 regularization. In: Proceedings of the 2013 SIAM international conference on data mining. SIAM, pp 103\u2013111","DOI":"10.1137\/1.9781611972832.12"},{"issue":"3","key":"4385_CR29","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1007\/s10618-012-0266-x","volume":"26","author":"F Gullo","year":"2013","unstructured":"Gullo F, Domeniconi C, Tagarelli A (2013) Projective clustering ensembles. Data Min Knowl Disc 26(3):452\u2013511","journal-title":"Data Min Knowl Disc"},{"key":"4385_CR30","doi-asserted-by":"crossref","unstructured":"Cho H, Dhillon IS, Guan Y, Sra S (2004) Minimum sum-squared residue co-clustering of gene expression data. In: Proceedings of the 2004 SIAM international conference on data mining. SIAM, pp 114\u2013125","DOI":"10.1137\/1.9781611972740.11"},{"issue":"Dec","key":"4385_CR31","first-page":"583","volume":"3","author":"A Strehl","year":"2002","unstructured":"Strehl A, Ghosh J (2002) Cluster ensembles\u2014a knowledge reuse framework for combining multiple partitions. Journal of machine learning research 3(Dec):583\u2013617","journal-title":"Journal of machine learning research"},{"key":"4385_CR32","doi-asserted-by":"publisher","first-page":"1009","DOI":"10.1016\/j.knosys.2018.10.022","volume":"163","author":"H Wang","year":"2019","unstructured":"Wang H, Yang Y, Liu B, Fujita H (2019) A study of graph-based system for multi-view clustering. Knowl-Based Syst 163:1009\u20131019","journal-title":"Knowl-Based Syst"},{"key":"4385_CR33","doi-asserted-by":"publisher","first-page":"105102","DOI":"10.1016\/j.knosys.2019.105102","volume":"189","author":"Z Kang","year":"2020","unstructured":"Kang Z, Shi G, Huang S, Chen W, Pu X, Zhou JT, Xu Z (2020) Multi-graph fusion for multi-view spectral clustering. Knowl-Based Syst 189:105102","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"4385_CR34","doi-asserted-by":"publisher","first-page":"1116","DOI":"10.1109\/TKDE.2019.2903810","volume":"32","author":"H Wang","year":"2019","unstructured":"Wang H, Yang Y, Liu B (2019) Gmc: graph-based multi-view clustering. IEEE Trans Knowl Data Eng 32(6):1116\u20131129","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"4385_CR35","doi-asserted-by":"crossref","unstructured":"Chen M-S, Huang L, Wang C-D, Huang D (2020) Multi-view clustering in latent embedding space. In: Proceedings of the AAAI conference on artificial intelligence, vol 34, pp 3513\u20133520","DOI":"10.1609\/aaai.v34i04.5756"},{"key":"4385_CR36","doi-asserted-by":"crossref","unstructured":"Fei-Fei L, Fergus R, Perona P (2004) Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In: 2004 conference on computer vision and pattern recognition workshop. IEEE, pp 178\u2013178","DOI":"10.1109\/CVPR.2004.383"},{"key":"4385_CR37","doi-asserted-by":"crossref","unstructured":"Bisson G, Grimal C (2012) Co-clustering of multi-view datasets: a parallelizable approach. In: 2012 IEEE 12th international conference on data mining. IEEE, pp 828\u2013833","DOI":"10.1109\/ICDM.2012.93"},{"key":"4385_CR38","doi-asserted-by":"crossref","unstructured":"Cai D, Zhang C, He X (2010) Unsupervised feature selection for multi-cluster data. In: Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining. KDD \u201910. Association for Computing Machinery, pp 333\u2013342","DOI":"10.1145\/1835804.1835848"},{"issue":"1","key":"4385_CR39","doi-asserted-by":"publisher","first-page":"1046","DOI":"10.1038\/s41598-017-01064-0","volume":"7","author":"G Yu","year":"2017","unstructured":"Yu G, Yu X, Wang J (2017) Network-aided bi-clustering for discovering cancer subtypes. Sci Rep 7(1):1046","journal-title":"Sci Rep"},{"key":"4385_CR40","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s10618-006-0060-8","volume":"14","author":"C Domeniconi","year":"2007","unstructured":"Domeniconi C, Gunopulos D, Ma S, Yan B, Al-Razgan M, Papadopoulos D (2007) Locally adaptive metrics for clustering high dimensional data. Data Min Knowl Discov 14:63\u201397","journal-title":"Data Min Knowl Discov"},{"issue":"1","key":"4385_CR41","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1137\/0105003","volume":"5","author":"J Munkres","year":"1957","unstructured":"Munkres J (1957) Algorithms for the assignment and transportation problems. J Soc Ind Appl Math 5(1):32\u201338","journal-title":"J Soc Ind Appl Math"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-04385-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-04385-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-04385-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T05:14:01Z","timestamp":1688188441000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-04385-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,20]]},"references-count":41,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["4385"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-04385-4","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,20]]},"assertion":[{"value":"4 December 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 December 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}