{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T11:34:47Z","timestamp":1783683287629,"version":"3.55.0"},"publisher-location":"Berlin, Heidelberg","reference-count":21,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783642352294","type":"print"},{"value":"9783642352300","type":"electronic"}],"license":[{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-35230-0_1","type":"book-chapter","created":{"date-parts":[[2012,12,13]],"date-time":"2012-12-13T05:39:19Z","timestamp":1355377159000},"page":"1-12","source":"Crossref","is-referenced-by-count":3,"title":["How to Visualize Large Data Sets?"],"prefix":"10.1007","author":[{"given":"Barbara","family":"Hammer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrej","family":"Gisbrecht","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Schulz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"1_CR1","unstructured":"Bengio, Y., Paiement, J.-F., Vincent, P., Delalleau, O., Roux, N.L., Ouimet, M.: Out-of-sample extensions for lle, isomap, mds, eigenmaps, and spectral clustering. In: Advances in Neural Information Processing Systems, pp. 177\u2013184. MIT Press (2004)"},{"key":"1_CR2","unstructured":"Biehl, M., Hammer, B., Mer\u00e9nyi, E., Sperduti, A., Villmann, T.: Learning in the context of very high dimensional data (Dagstuhl Seminar 11341), vol.\u00a01 (2011)"},{"key":"1_CR3","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1162\/089976698300017953","volume":"10","author":"C.M. Bishop","year":"1998","unstructured":"Bishop, C.M., Svens\u00e9n, M., Williams, C.K.I.: Gtm: The generative topographic mapping. Neural Computation\u00a010, 215\u2013234 (1998)","journal-title":"Neural Computation"},{"issue":"3","key":"1_CR4","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1162\/NECO_a_00250","volume":"24","author":"K. Bunte","year":"2012","unstructured":"Bunte, K., Biehl, M., Hammer, B.: A general framework for dimensionality reducing data visualization mapping. Neural Computation\u00a024(3), 771\u2013804 (2012)","journal-title":"Neural Computation"},{"issue":"9","key":"1_CR5","doi-asserted-by":"publisher","first-page":"1359","DOI":"10.1016\/j.neucom.2010.12.011","volume":"74","author":"A. Gisbrecht","year":"2011","unstructured":"Gisbrecht, A., Hammer, B.: Relevance learning in generative topographic mapping. Neurocomputing\u00a074(9), 1359\u20131371 (2011)","journal-title":"Neurocomputing"},{"key":"1_CR6","doi-asserted-by":"crossref","unstructured":"Gisbrecht, A., Hammer, B., Schleif, F.-M., Zhu, X.: Accelerating dissimilarity clustering for biomedical data analysis. In: IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp. 154\u2013161 (2011)","DOI":"10.1109\/CIBCB.2011.5948460"},{"key":"1_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1007\/978-3-642-34156-4_13","volume-title":"Advances in Intelligent Data Analysis XI","author":"A. Gisbrecht","year":"2012","unstructured":"Gisbrecht, A., Hofmann, D., Hammer, B.: Discriminative Dimensionality Reduction Mappings. In: Hollm\u00e9n, J., Klawonn, F., Tucker, A. (eds.) IDA 2012. LNCS, vol.\u00a07619, pp. 126\u2013138. Springer, Heidelberg (2012)"},{"key":"1_CR8","unstructured":"Gisbrecht, A., Lueks, W., Mokbel, B., Hammer, B.: Out-of-sample kernel extensions for nonparametric dimensionality reduction. In: ESANN 2012, pp. 531\u2013536 (2012)"},{"key":"1_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-21566-7_1","volume-title":"Advances in Self-Organizing Maps","author":"B. Hammer","year":"2011","unstructured":"Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F.-M., Zhu, X.: Topographic Mapping of Dissimilarity Data. In: Laaksonen, J., Honkela, T. (eds.) WSOM 2011. LNCS, vol.\u00a06731, pp. 1\u201315. Springer, Heidelberg (2011)"},{"issue":"9","key":"1_CR10","doi-asserted-by":"publisher","first-page":"2229","DOI":"10.1162\/NECO_a_00012","volume":"22","author":"B. Hammer","year":"2010","unstructured":"Hammer, B., Hasenfuss, A.: Topographic mapping of large dissimilarity datasets. Neural Computation\u00a022(9), 2229\u20132284 (2010)","journal-title":"Neural Computation"},{"key":"1_CR11","doi-asserted-by":"publisher","first-page":"936","DOI":"10.1109\/72.935102","volume":"12","author":"S. Kaski","year":"2001","unstructured":"Kaski, S., Sinkkonen, J., Peltonen, J.: Bankruptcy analysis with self-organizing maps in learning metrics. IEEE Transactions on Neural Networks\u00a012, 936\u2013947 (2001)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"1_CR12","doi-asserted-by":"crossref","unstructured":"Kohonen, T.: Self-Organizing Maps. Springer (2000)","DOI":"10.1007\/978-3-642-56927-2"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Lee, J.A., Verleysen, M.: Nonlinear dimensionality redcution. Springer (2007)","DOI":"10.1007\/978-0-387-39351-3"},{"key":"1_CR14","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.1016\/j.neunet.2004.06.008","volume":"17","author":"J. Peltonen","year":"2004","unstructured":"Peltonen, J., Klami, A., Kaski, S.: Improved learning of riemannian metrics for exploratory analysis. Neural Networks\u00a017, 1087\u20131100 (2004)","journal-title":"Neural Networks"},{"key":"1_CR15","doi-asserted-by":"publisher","first-page":"3532","DOI":"10.1162\/neco.2009.11-08-908","volume":"21","author":"P. Schneider","year":"2009","unstructured":"Schneider, P., Biehl, M., Hammer, B.: Adaptive relevance matrices in learning vector quantization. Neural Computation\u00a021, 3532\u20133561 (2009)","journal-title":"Neural Computation"},{"key":"1_CR16","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1111\/1467-9868.00196","volume":"61","author":"M.E. Tipping","year":"1999","unstructured":"Tipping, M.E., Bishop, C.M.: Probabilistic principal component analysis. Journal of the Royal Statistical Society, Series B\u00a061, 611\u2013622 (1999)","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"1_CR17","first-page":"2579","volume":"9","author":"L. van der Maaten","year":"2008","unstructured":"van der Maaten, L., Hinton, G.: Visualizing high-dimensional data using t-sne. Journal of Machine Learning Research\u00a09, 2579\u20132605 (2008)","journal-title":"Journal of Machine Learning Research"},{"key":"1_CR18","unstructured":"van der Maaten, L., Postma, E., van den Herik, H.: Dimensionality reduction: A comparative review. Technical report, Tilburg University Technical Report, TiCC-TR 2009-005 (2009)"},{"key":"1_CR19","first-page":"451","volume":"11","author":"J. Venna","year":"2010","unstructured":"Venna, J., Peltonen, J., Nybo, K., Aidos, H., Kaski, S.: Information retrieval perspective to nonlinear dimensionality reduction for data visualization. Journal of Machine Learning Research\u00a011, 451\u2013490 (2010)","journal-title":"Journal of Machine Learning Research"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Ward, M., Grinstein, G., Keim, D.A.: Interactive Data Visualization: Foundations, Techniques, and Application. A. K. Peters, Ltd. (2010)","DOI":"10.1201\/b10683"},{"issue":"6-7","key":"1_CR21","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1016\/j.neunet.2006.05.007","volume":"19","author":"H. Yin","year":"2006","unstructured":"Yin, H.: On the equivalence between kernel self-organising maps and self-organising mixture density networks. Neural Networks\u00a019(6-7), 780\u2013784 (2006)","journal-title":"Neural Networks"}],"container-title":["Advances in Intelligent Systems and Computing","Advances in Self-Organizing Maps"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-35230-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T14:42:43Z","timestamp":1674830563000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-642-35230-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642352294","9783642352300"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-35230-0_1","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013]]}}}