{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T20:55:16Z","timestamp":1764276916589},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319973036"},{"type":"electronic","value":"9783319973043"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-97304-3_64","type":"book-chapter","created":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T14:34:06Z","timestamp":1532615646000},"page":"837-850","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Semi-supervised DenPeak Clustering with Pairwise Constraints"],"prefix":"10.1007","author":[{"given":"Yazhou","family":"Ren","sequence":"first","affiliation":[]},{"given":"Xiaohui","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Ke","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Guoxian","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Dezhong","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Zenglin","family":"Xu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,27]]},"reference":[{"key":"64_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1007\/978-3-540-28651-6_30","volume-title":"Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2004","author":"F Angiulli","year":"2004","unstructured":"Angiulli, F., Pizzuti, C., Ruffolo, M.: DESCRY: a density based clustering algorithm for very large data sets. In: Yang, Z.R., Yin, H., Everson, R.M. (eds.) IDEAL 2004. LNCS, vol. 3177, pp. 203\u2013210. Springer, Heidelberg (2004). \nhttps:\/\/doi.org\/10.1007\/978-3-540-28651-6_30"},{"issue":"2","key":"64_CR2","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1145\/304181.304187","volume":"28","author":"Mihael Ankerst","year":"1999","unstructured":"Ankerst, M., Breunig, M.M., Kriegel, H.P., Sander, J.: OPTICS: ordering points to identify the clustering structure. In: ACM SIGMOD, pp. 49\u201360. ACM (1999)","journal-title":"ACM SIGMOD Record"},{"key":"64_CR3","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1137\/1.9781611972740.31","volume-title":"Proceedings of the 2004 SIAM International Conference on Data Mining","author":"Sugato Basu","year":"2004","unstructured":"Basu, S., Banerjee, A., Mooney, R.J.: Active semi-supervision for pairwise constrained clustering. In: SIAM International Conference on Data Mining, pp. 333\u2013344 (2004)"},{"key":"64_CR4","unstructured":"Bradley, P., Bennett, K., Demiriz, A.: Constrained k-means clustering, pp. 1\u20138. Microsoft Research, Redmond (2000)"},{"issue":"3","key":"64_CR5","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1007\/s10618-013-0311-4","volume":"27","author":"RJGB Campello","year":"2013","unstructured":"Campello, R.J.G.B., Moulavi, D., Zimek, A., Sander, J.: A framework for semi-supervised and unsupervised optimal extraction of clusters from hierarchies. Data Min. Knowl. Discov. 27(3), 344\u2013371 (2013)","journal-title":"Data Min. Knowl. Discov."},{"issue":"5","key":"64_CR6","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/34.1000236","volume":"24","author":"D Comaniciu","year":"2002","unstructured":"Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Mach. Intell. 24(5), 603\u2013619 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"64_CR7","doi-asserted-by":"publisher","first-page":"72","DOI":"10.3390\/ijgi5050072","volume":"5","author":"Q Du","year":"2016","unstructured":"Du, Q., Dong, Z., Huang, C., Ren, F.: Density-based clustering with geographical background constraints using a semantic expression model. ISPRS Int. J. Geo-Inf. 5(5), 72 (2016)","journal-title":"ISPRS Int. J. Geo-Inf."},{"key":"64_CR8","unstructured":"Ester, M., Kriegel, H.P., Sander, J., Xu, X., et al.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, pp. 226\u2013231 (1996)"},{"key":"64_CR9","doi-asserted-by":"crossref","unstructured":"Fan, W.Q., Wang, C.D., Lai, J.H.: SDenPeak: semi-supervised nonlinear clustering based on density and distance. In: Proceedings of 2016 IEEE Second International Conference on Big Data Computing Service and Applications, pp. 269\u2013275. IEEE (2016)","DOI":"10.1109\/BigDataService.2016.43"},{"key":"64_CR10","first-page":"1","volume":"63","author":"Y Gu","year":"2017","unstructured":"Gu, Y., Ye, X., Zhang, F., Du, Z., Liu, R., Yu, L.: A parallel varied density-based clustering algorithm with optimized data partition. J. Spat. Sci. 63, 1\u201322 (2017)","journal-title":"J. Spat. Sci."},{"key":"64_CR11","unstructured":"Hinneburg, A., Keim, D.A., et al.: An efficient approach to clustering in large multimedia databases with noise. In: KDD 1998, pp. 58\u201365 (1998)"},{"key":"64_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.072","author":"S Huang","year":"2018","unstructured":"Huang, S., Ren, Y., Xu, Z.: Robust multi-view data clustering with multi-view capped-norm k-means. Neurocomputing (2018). \nhttps:\/\/doi.org\/10.1016\/j.neucom.2018.05.072","journal-title":"Neurocomputing"},{"issue":"2","key":"64_CR13","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/s10618-017-0543-9","volume":"32","author":"S Huang","year":"2018","unstructured":"Huang, S., Wang, H., Li, T., Li, T., Xu, Z.: Robust graph regularized nonnegative matrix factorization for clustering. Data Min. Knowl. Discov. 32(2), 483\u2013503 (2018)","journal-title":"Data Min. Knowl. Discov."},{"issue":"3","key":"64_CR14","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"AK Jain","year":"1999","unstructured":"Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: a review. ACM Comput. Surv. 31(3), 264\u2013323 (1999)","journal-title":"ACM Comput. Surv."},{"key":"64_CR15","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.neucom.2015.05.109","volume":"171","author":"Y Lv","year":"2016","unstructured":"Lv, Y., et al.: An efficient and scalable density-based clustering algorithm for datasets with complex structures. Neurocomputing 171, 9\u201322 (2016)","journal-title":"Neurocomputing"},{"key":"64_CR16","unstructured":"MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281\u2013297. University of California Press (1967)"},{"issue":"2","key":"64_CR17","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1007\/s10115-014-0797-0","volume":"45","author":"ST Mai","year":"2015","unstructured":"Mai, S.T., He, X., Feng, J., Plant, C., B\u00f6hm, C.: Anytime density-based clustering of complex data. Knowl. Inf. Syst. 45(2), 319\u2013355 (2015)","journal-title":"Knowl. Inf. Syst."},{"key":"64_CR18","doi-asserted-by":"crossref","unstructured":"Ren, Y., Domeniconi, C., Zhang, G., Yu, G.: Weighted-object ensemble clustering. In: Proceedings of the IEEE International Conference on Data Mining, pp. 627\u2013636. IEEE (2013)","DOI":"10.1109\/ICDM.2013.80"},{"key":"64_CR19","doi-asserted-by":"publisher","first-page":"794","DOI":"10.1137\/1.9781611973440.91","volume-title":"Proceedings of the 2014 SIAM International Conference on Data Mining","author":"Yazhou Ren","year":"2014","unstructured":"Ren, Y., Domeniconi, C., Zhang, G., Yu, G.: A weighted adaptive mean shift clustering algorithm. In: SIAM International Conference on Data Mining, pp. 794\u2013802 (2014)"},{"issue":"2","key":"64_CR20","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1007\/s10115-016-0988-y","volume":"51","author":"Y Ren","year":"2017","unstructured":"Ren, Y., Domeniconi, C., Zhang, G., Yu, G.: Weighted-object ensemble clustering: methods and analysis. Knowl. Inf. Syst. 51(2), 661\u2013689 (2017)","journal-title":"Knowl. Inf. Syst."},{"key":"64_CR21","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1007\/978-3-662-44851-9_41","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Y Ren","year":"2014","unstructured":"Ren, Y., Kamath, U., Domeniconi, C., Zhang, G.: Boosted mean shift clustering. In: Calders, T., Esposito, F., H\u00fcllermeier, E., Meo, R. (eds.) ECML PKDD 2014. LNCS (LNAI), vol. 8725, pp. 646\u2013661. Springer, Heidelberg (2014). \nhttps:\/\/doi.org\/10.1007\/978-3-662-44851-9_41"},{"key":"64_CR22","doi-asserted-by":"crossref","unstructured":"Ren, Y., Zhang, G., Yu, G.: Random subspace based semi-supervised feature selection. In: International Conference on Machine Learning and Cybernetics, pp. 113\u2013118 (2011)","DOI":"10.1109\/ICMLC.2011.6016706"},{"issue":"6191","key":"64_CR23","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez, A., Laio, A.: Clustering by fast search and find of density peaks. Science 344(6191), 1492\u20131496 (2014)","journal-title":"Science"},{"key":"64_CR24","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1007\/978-3-540-72530-5_25","volume-title":"Rough Sets, Fuzzy Sets, Data Mining and Granular Computing","author":"C Ruiz","year":"2007","unstructured":"Ruiz, C., Spiliopoulou, M., Menasalvas, E.: C-DBSCAN: density-based clustering with constraints. In: An, A., Stefanowski, J., Ramanna, S., Butz, C.J., Pedrycz, W., Wang, G. (eds.) RSFDGrC 2007. LNCS (LNAI), vol. 4482, pp. 216\u2013223. Springer, Heidelberg (2007). \nhttps:\/\/doi.org\/10.1007\/978-3-540-72530-5_25"},{"issue":"3","key":"64_CR25","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/s10618-009-0157-y","volume":"21","author":"C Ruiz","year":"2010","unstructured":"Ruiz, C., Spiliopoulou, M., Menasalvas, E.: Density-based semi-supervised clustering. Data Min. Knowl. Discov. 21(3), 345\u2013370 (2010)","journal-title":"Data Min. Knowl. Discov."},{"key":"64_CR26","unstructured":"Wagstaff, K., Cardie, C., Rogers, S., Schr\u00f6dl, S., et al.: Constrained k-means clustering with background knowledge. In: ICML, pp. 577\u2013584 (2001)"},{"issue":"3","key":"64_CR27","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1109\/TNN.2005.845141","volume":"16","author":"R Xu","year":"2005","unstructured":"Xu, R., Wunsch, D.: Survey of clustering algorithms. IEEE Trans. Neural Netw. 16(3), 645\u2013678 (2005)","journal-title":"IEEE Trans. Neural Netw."},{"key":"64_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1007\/978-3-319-70087-8_71","volume-title":"Neural Information Processing","author":"Y Yu","year":"2017","unstructured":"Yu, Y., Yu, G., Chen, X., Ren, Y.: Semi-supervised multi-label linear discriminant analysis. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, E.S. (eds.) ICONIP 2017. LNCS, vol. 10634, pp. 688\u2013698. Springer, Cham (2017)"},{"key":"64_CR29","unstructured":"Zhu, X.: Semi-supervised learning literature survey. Technical report 1530, Computer Sciences, University of Wisconsin-Madison (2005)"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2018: Trends in Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-97304-3_64","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T15:16:56Z","timestamp":1532618216000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-97304-3_64"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319973036","9783319973043"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-97304-3_64","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}