{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:36:26Z","timestamp":1742913386762,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319180311"},{"type":"electronic","value":"9783319180328"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"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":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-18032-8_9","type":"book-chapter","created":{"date-parts":[[2015,5,8]],"date-time":"2015-05-08T05:41:54Z","timestamp":1431063714000},"page":"106-118","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Spectral Clustering for Large-Scale Social Networks via a Pre-Coarsening Sampling based Nystr\u00d6m Method"],"prefix":"10.1007","author":[{"given":"Ying","family":"Kang","sequence":"first","affiliation":[]},{"given":"Bo","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Weiping","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Dan","family":"Meng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,5,9]]},"reference":[{"key":"9_CR1","unstructured":"Ng, A.Y., Jordan, M.I., Weiss, Y.: On Spectral Clustering: Analysis and an Algorithm. Advances in Neural Information Processing Systems (2002)"},{"key":"9_CR2","unstructured":"Bellman, R., Bellman, R.E., et al.: Introduction to Matrix Analysis (1970)"},{"key":"9_CR3","unstructured":"Williams, C., Seeger, M.: Using the nystr\u00f6m method to speed up kernel machines. In: Proceedings of the 14th Annual Conference on Neural Information Processing Systems (2001)"},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Drineas, P., Mahoney, M.W.: On the Nystr\u00f6m Method for Approximating a Gram Matrix for Improved Kernel-based Learning. The Journal of Machine Learning Research (2005)","DOI":"10.1007\/11503415_22"},{"key":"9_CR5","volume-title":"DBRS: A Density-based Spatial Clustering Method with Random Sampling","author":"X Wang","year":"2003","unstructured":"Wang, X., Hamilton, H.J.: DBRS: A Density-based Spatial Clustering Method with Random Sampling. Springer, Heidelberg (2003)"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Zhang, K., Tsang, I.W., Kwok, J.T.: Improved nystr\u00f6m low-rank approximation and error analysis. In: Proceedings of the International Conference on Machine Learning (2008)","DOI":"10.1145\/1390156.1390311"},{"key":"9_CR7","doi-asserted-by":"crossref","unstructured":"Kumpula, J.M., Kivel\u00e4, M., Kaski, K., Saram\u00e4ki, J.: Sequential Algorithm for Fast Clique Percolation. Phys. Rev. (2008)","DOI":"10.1103\/PhysRevE.78.026109"},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Xiang, T., et al.: Spectral Clustering with Eigenvector Selection. Pattern Recognition(2008)","DOI":"10.1016\/j.patcog.2007.07.023"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Von Luxburg, U.: A Tutorial on Spectral Clustering. Statistics and Computing (2007)","DOI":"10.1007\/s11222-007-9033-z"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Yan, D., Huang, L., Jordan, M.I.: Fast approximate spectral clustering. In: Proceedings of the ACM SIGKDD (2009)","DOI":"10.1145\/1557019.1557118"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Mall, R., Langone, R., Suykens, J.A.K.: Kernel Spectral Clustering for Big Data Networks. Entropy (2013)","DOI":"10.1109\/BigData.2013.6691599"},{"key":"9_CR12","unstructured":"Sun, Z.H., Wei, X.H., Zhou, W.H.: A Nystr\u00f6m-based Subtractive Clustering Method. Wavelet Active Media Technology and Information Processing (ICWAMTIP) (2012)"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Fowlkes, C., Belongie, S., Chung, F., et al.: Spectral Grouping Using the Nystr\u00f6m Method. IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)","DOI":"10.1109\/TPAMI.2004.1262185"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Belabbas, M.A., Wolfe, P.J.: Spectral methods in machine learning and new strategies for very large datasets. In: Proceedings of the National Academy of Sciences (2009)","DOI":"10.1073\/pnas.0810600105"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Dick, J., Kritzer, P., et al.: Lattice-Nystr\u00f6m Method for Fredholm Integral Equations of the Second Kind with Convolution Type kernels. Journal of Complexity (2007)","DOI":"10.1016\/j.jco.2007.03.004"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Belongie, S., Fowlkes, C., Chung, F., et al.: Spectral Partitioning with Indefinite Kernels Using the Nystr\u00f6m Extension. European Conference on Computer Vision (2002)","DOI":"10.1007\/3-540-47977-5_35"},{"key":"9_CR17","unstructured":"Adamic, L.A., Adar, E.: You are what you link. In: The 10th Annual International World Wide Web Conference, Hong Kong (2001)"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Palla, G., Der\u00e9nyi, I., Farkas, I., Vicsek, T.: Uncovering the Overlapping Community Structure of Complex Networks in Nature and Society. Nature (2005)","DOI":"10.1038\/nature03607"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Yang, J., Leskovec, J.: Defining and evaluating network communities based on ground-truth. In: Proceedings of ACM SIGKDD (2012)","DOI":"10.1145\/2350190.2350193"},{"key":"9_CR20","unstructured":"Bengio, Y., Paiement, J.F., et al.: Out-of-Sample Extensions for Lle, Isomap, Mds, Eigen-maps and Spectral Clustering. Advances in Neural Information Processing Systems (2004)"},{"key":"9_CR21","doi-asserted-by":"crossref","unstructured":"Choromanska, A., Jebara, T., Kim, H., et al.: Fast Spectral Clustering via the Nystr\u00f6m Method. Algorithmic Learning Theory (2013)","DOI":"10.1007\/978-3-642-40935-6_26"},{"key":"9_CR22","unstructured":"Xianchao, Z., Quanzeng, Y.: Clusterability analysis and incremental sampling for nystr\u00f6m extension based spectral clustering. In: International Conference on Data Mining (2011)"},{"key":"9_CR23","doi-asserted-by":"crossref","unstructured":"Danon, L., Duch, J., Diaz-Guilera, A., Arenas, A.: Comparing Community Structure Identification. Stat. Mech. (2005)","DOI":"10.1088\/1742-5468\/2005\/09\/P09008"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-18032-8_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T07:36:00Z","timestamp":1676446560000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-18032-8_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319180311","9783319180328"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-18032-8_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"9 May 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}