LEADER 05489nam 22008775 450 001 996466251103316 005 20200702041605.0 010 $a3-642-01805-X 024 7 $a10.1007/978-3-642-01805-3 035 $a(CKB)1000000000746062 035 $a(SSID)ssj0000320042 035 $a(PQKBManifestationID)11224642 035 $a(PQKBTitleCode)TC0000320042 035 $a(PQKBWorkID)10343267 035 $a(PQKB)10541478 035 $a(DE-He213)978-3-642-01805-3 035 $a(MiAaPQ)EBC3064204 035 $a(PPN)136301096 035 $a(EXLCZ)991000000000746062 100 $a20100301d2009 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aSimilarity-Based Clustering$b[electronic resource] $eRecent Developments and Biomedical Applications /$fedited by Thomas Villmann, M. Biehl, Barbara Hammer, Michel Verleysen 205 $a1st ed. 2009. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2009. 215 $a1 online resource (XI, 203 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v5400 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-01804-1 320 $aIncludes bibliographical references and index. 327 $aI: Dynamics of Similarity-Based Clustering -- Statistical Mechanics of On-line Learning -- Some Theoretical Aspects of the Neural Gas Vector Quantizer -- Immediate Reward Reinforcement Learning for Clustering and Topology Preserving Mappings -- II: Information Representation -- Advances in Feature Selection with Mutual Information -- Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data -- Median Topographic Maps for Biomedical Data Sets -- Visualization of Structured Data via Generative Probabilistic Modeling -- III: Particular Challenges in Applications -- Learning Highly Structured Manifolds: Harnessing the Power of SOMs -- Estimation of Boar Sperm Status Using Intracellular Density Distribution in Grey Level Images -- HIV-1 Drug Resistance Prediction and Therapy Optimization: A Case Study for the Application of Classification and Clustering Methods. 330 $aThis book is the outcome of the Dagstuhl Seminar on "Similarity-Based Clustering" held at Dagstuhl Castle, Germany, in Spring 2007. In three chapters, the three fundamental aspects of a theoretical background, the representation of data and their connection to algorithms, and particular challenging applications are considered. Topics discussed concern a theoretical investigation and foundation of prototype based learning algorithms, the development and extension of models to directions such as general data structures and the application for the domain of medicine and biology. Similarity based methods find widespread applications in diverse application domains, including biomedical problems, but also in remote sensing, geoscience or other technical domains. The presentations give a good overview about important research results in similarity-based learning, whereby the character of overview articles with references to correlated research articles makes the contributions particularly suited for a first reading concerning these topics. 410 0$aLecture Notes in Artificial Intelligence ;$v5400 606 $aLife sciences 606 $aBioinformatics 606 $aMedicine 606 $aData mining 606 $aInformation storage and retrieval 606 $aOptical data processing 606 $aLife Sciences, general$3https://scigraph.springernature.com/ontologies/product-market-codes/L00004 606 $aComputational Biology/Bioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23050 606 $aBiomedicine, general$3https://scigraph.springernature.com/ontologies/product-market-codes/B0000X 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 608 $aDagstuhl (2007)$2swd 608 $aKongress.$2swd 615 0$aLife sciences. 615 0$aBioinformatics. 615 0$aMedicine. 615 0$aData mining. 615 0$aInformation storage and retrieval. 615 0$aOptical data processing. 615 14$aLife Sciences, general. 615 24$aComputational Biology/Bioinformatics. 615 24$aBiomedicine, general. 615 24$aData Mining and Knowledge Discovery. 615 24$aInformation Storage and Retrieval. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 676 $a570 686 $aBIO 110f$2stub 686 $aDAT 708f$2stub 686 $aDAT 758f$2stub 686 $aDAT 777f$2stub 686 $aSS 4800$2rvk 702 $aVillmann$b Thomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBiehl$b M$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHammer$b Barbara$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVerleysen$b Michel$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996466251103316 996 $aSimilarity-Based Clustering$9774168 997 $aUNISA