{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T04:24:11Z","timestamp":1792729451283,"version":"4.5.0"},"publisher-location":"Berlin, Heidelberg","reference-count":16,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783540292449","type":"print"},{"value":"9783540316657","type":"electronic"}],"license":[{"start":{"date-parts":[[2005,1,1]],"date-time":"2005-01-01T00:00:00Z","timestamp":1104537600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2005]]},"DOI":"10.1007\/11564126_11","type":"book-chapter","created":{"date-parts":[[2005,11,4]],"date-time":"2005-11-04T05:24:55Z","timestamp":1131081895000},"page":"59-70","source":"Crossref","is-referenced-by-count":160,"title":["Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results"],"prefix":"10.1007","author":[{"given":"Ian","family":"Davidson","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. S.","family":"Ravi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"11_CR1","unstructured":"Basu, S., Banerjee, A., Mooney, R.: Semi-supervised Clustering by Seeding. In: 19\n                    th\n                   ICML (2002)"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Basu, S., Bilenko, M., Mooney, R.J.: Active Semi-Supervision for Pairwise Constrained Clustering. 4\n                    th\n                   SIAM Data Mining Conf. (2004)","DOI":"10.1137\/1.9781611972740.31"},{"key":"11_CR3","unstructured":"Bradley, P., Fayyad, U., Reina, C.: Scaling Clustering Algorithms to Large Databases. In: 4\n                    th\n                   ACM KDD Conference (1998)"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Davidson, I., Ravi, S.S.: Clustering with Constraints: Feasibility Issues and the k-Means Algorithm. In: SIAM International Conference on Data Mining (2005)","DOI":"10.1137\/1.9781611972757.13"},{"key":"11_CR5","unstructured":"Davidson, I., Ravi, S.S.: Towards Efficient and Improved Hierarchical Clustering with Instance and Cluster-Level Constraints. Tech. Report, CS Department, SUNY - Albany (2005), Available from \n                    \n                      www.cs.albany.edu\/~davidson"},{"key":"11_CR6","unstructured":"Elkan, C.: Using the triangle inequality to accelerate k-means. ICML (2003)"},{"key":"11_CR7","volume-title":"Computers and Intractability: A Guide to the Theory of NP-completeness","author":"M. Garey","year":"1979","unstructured":"Garey, M., Johnson, D.: Computers and Intractability: A Guide to the Theory of NP-completeness. Freeman and Co., New York (1979)"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Garey, M., Johnson, D., Witsenhausen, H.: The complexity of the generalized Lloyd-Max problem. IEEE Trans. Information Theory\u00a028(2) (1982)","DOI":"10.1109\/TIT.1982.1056488"},{"key":"11_CR9","unstructured":"Klein, D., Kamvar, S.D., Manning, C.D.: From Instance-Level Constraints to Space-Level Constraints: Making the Most of Prior Knowledge in Data Clustering. ICML (2002)"},{"key":"11_CR10","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1007\/11430919_45","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"M. Nanni","year":"2005","unstructured":"Nanni, M.: Speeding-up hierarchical agglomerative clustering in presence of expensive metrics. In: Ho, T.-B., Cheung, D., Liu, H. (eds.) PAKDD 2005. LNCS (LNAI), vol.\u00a03518, pp. 378\u2013387. Springer, Heidelberg (2005)"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Schafer, T.J.: The Complexity of Satisfiability Problems. STOC (1978)","DOI":"10.1145\/800133.804350"},{"key":"11_CR12","unstructured":"Wagstaff, K., Cardie, C.: Clustering with Instance-Level Constraints. ICML (2000)"},{"key":"11_CR13","volume-title":"Introduction to Graph Theory","author":"D.B. West","year":"2001","unstructured":"West, D.B.: Introduction to Graph Theory, 2nd edn. Prentice-Hall, Englewood Cliffs (2001)","edition":"2"},{"key":"11_CR14","unstructured":"Yang, K., Yang, R., Kafatos, M.: A Feasible Method to Find Areas with Constraints Using Hierarchical Depth-First Clustering. In: Scientific and Stat. Database Management Conf. (2001)"},{"key":"11_CR15","unstructured":"Zaiane, O.R., Foss, A., Lee, C., Wang, W.: On Data Clustering Analysis: Scalability, Constraints and Validation. PAKDD (2000)"},{"issue":"2","key":"11_CR16","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s10618-005-0361-3","volume":"10","author":"Y. Zho","year":"2005","unstructured":"Zho, Y., Karypis, G.: Hierarchical Clustering Algorithms for Document Datasets. Data Mining and Knowledge Discovery\u00a010(2), 141\u2013168 (2005)","journal-title":"Data Mining and Knowledge Discovery"}],"container-title":["Lecture Notes in Computer Science","Knowledge Discovery in Databases: PKDD 2005"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/11564126_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,19]],"date-time":"2019-05-19T13:39:28Z","timestamp":1558273168000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/11564126_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005]]},"ISBN":["9783540292449","9783540316657"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/11564126_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005]]}}}