Data science and classification
This volume contains a refereed selection of papers presented during the 10th Jubilee Conference of the International Federation of Classi?cation - cieties(IFCS)onDataScienceandClassi?cationheldattheFacultyofSocial Sciences of the University of Ljubljana in Slovenia, July 25-29, 2006. Papers submitt...
Salvato in:
| Autore principale: | |
|---|---|
| Altri autori: | |
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edizione: | 1st ed. 2006. |
| Serie: | Studies in Classification, Data Analysis, and Knowledge Organization
|
| Soggetti: | |
| Accesso online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Description d'après consultation du 17 mars 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Data science and classification, Texte imprimé, edited by Vladimir Batagelj, Hans-Hermann Bock, Anuška Ferligoj, Aleš Žiberna, Berlin, Springer, 2006 |
| LEADER | 06966nam a22003977a 4500 | ||
|---|---|---|---|
| 001 | 938601 | ||
| 008 | 080410q2000 xxe ||| |||| 00| 0 eng d | ||
| 009 | PPN123135095 | ||
| 020 | |a 9783540344162 | ||
| 041 | 0 | |a eng | |
| 082 | |a 519.5 | ||
| 100 | 1 | |a Batagelj, Vladimir, |d 1948- | |
| 245 | 1 | 0 | |a Data science and classification |c Vladimir Batagelj, Hans-Hermann Bock, Anuška Ferligoj,... [et al.]. |
| 250 | |a 1st ed. 2006. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Classification, Data Analysis, and Knowledge Organization |x 2198-3321 | |
| 500 | |a Description d'après consultation du 17 mars 2011 | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 504 | |a Notes bibliogr. Index | ||
| 505 | 1 | |a Similarity and Dissimilarity A Tree-Based Similarity for Evaluating Concept Proximities in an Ontology Improved Fréchet Distance for Time Series Comparison of Distance Indices Between Partitions Design of Dissimilarity Measures: A New Dissimilarity Between Species Distribution Areas Dissimilarities for Web Usage Mining Properties and Performance of Shape Similarity Measures Classification and Clustering Hierarchical Clustering for Boxplot Variables Evaluation of Allocation Rules Under Some Cost Constraints Crisp Partitions Induced by a Fuzzy Set Empirical Comparison of a Monothetic Divisive Clustering Method with the Ward and the k-means Clustering Methods Model Selection for the Binary Latent Class Model: A Monte Carlo Simulation Finding Meaningful and Stable Clusters Using Local Cluster Analysis Comparing Optimal Individual and Collective Assessment Procedures Network and Graph Analysis Some Open Problem Sets for Generalized Blockmodeling Spectral Clustering and Multidimensional Scaling: A Unified View Analyzing the Structure of U.S. Patents Network Identifying and Classifying Social Groups: A Machine Learning Approach Analysis of Symbolic Data Multidimensional Scaling of Histogram Dissimilarities Dependence and Interdependence Analysis for Interval-Valued Variables A New Wasserstein Based Distance for the Hierarchical Clustering of Histogram Symbolic Data Symbolic Clustering of Large Datasets A Dynamic Clustering Method for Mixed Feature-Type Symbolic Data General Data Analysis Methods Iterated Boosting for Outlier Detection Sub-species of Homopus Areolatus? Biplots and Small Class Inference with Analysis of Distance Revised Boxplot Based Discretization as the Kernel of Automatic Interpretation of Classes Using Numerical Variables Data and Web Mining Comparison of Two Methods for Detecting and Correcting Systematic Error in High-throughput Screening Data kNN Versus SVM in the Collaborative Filtering Framework Mining Association Rules in Folksonomies Empirical Analysis of Attribute-Aware Recommendation Algorithms with Variable Synthetic Data Patterns of Associations in Finite Sets of Items Analysis of Music Data Generalized N-gram Measures for Melodic Similarity Evaluating Different Approaches to Measuring the Similarity of Melodies Using MCMC as a Stochastic Optimization Procedure for Musical Time Series Local Models in Register Classification by Timbre Gene and Microarray Analysis Improving the Performance of Principal Components for Classification of Gene Expression Data Through Feature Selection A New Efficient Method for Assessing Missing Nucleotides in DNA Sequences in the Framework of a Generic Evolutionary Model New Efficient Algorithm for Modeling Partial and Complete Gene Transfer Scenarios | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a This volume contains a refereed selection of papers presented during the 10th Jubilee Conference of the International Federation of Classi?cation - cieties(IFCS)onDataScienceandClassi?cationheldattheFacultyofSocial Sciences of the University of Ljubljana in Slovenia, July 25-29, 2006. Papers submitted fortheconferenceweresubjectedtoa carefulreviewingprocess- volvingatleasttworeviewersper paper. As aresultofthis reviewingprocess, 37 papers were selected for publication in this volume. The book presents recent advances in data analysis, classi?cation and clustering from methodological, theoretical, or algorithmic points of view. It shows how data analysis methods can be applied in various subject-speci?c domains. Areas that receive particular attention in this book are similarity and dissimilarity analysis, discrimination and clustering, network and graph analysis, and the processing of symbolic data. Special sections are devoted to data and web mining and to the application of data analysis methods in quantitative musicology and microbiology. Readers will ?nd a ?ne selection of recent technical and application-orientedpapers that characterizethe c- rent developments in data science and classi?cation. The combination of new methodologicaladvances with the wide rangeof real applicationscollected in this volumewill be ofspecialvaluefor researcherswhen choosingappropriate newly developed analytical tools for their research problems in classi?cation and data analysis. The editors are grateful to the authors of the papers in this volume for their contributions and for their willingness to respond so positively to the time constraintsin preparingthe ?nal versionsof their papers. Without their worktherewouldbenobook. Weareespeciallygratefultothereferees listed at the end of this book who reviewed the submitted papers. Their careful reviews helped us greatly in selecting the papers included in this volume | ||
| 650 | |a Bases de données | ||
| 650 | |a Reconnaissance optique des formes (informatique) | ||
| 650 | |a Classification automatique | ||
| 700 | 1 | |a Ferligoj, Anuska, |d 19..- |4 edt | |
| 776 | 0 | |t Data science and classification |b Texte imprimé |f edited by Vladimir Batagelj, Hans-Hermann Bock, Anuška Ferligoj, Aleš Žiberna |c Berlin |n Springer |d 2006 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/3-540-34416-0 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-6R0KQ3JG-D |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:747897328 |u https://ezproxy.univ-orleans.fr/login?url=https://dx.doi.org/10.1007/3-540-34416-0 |z Accès Université d'Orléans | |
| 856 | 4 | |5 180339901:750910356 |u https://ezproxy.insa-cvl.fr/login?qurl=https://dx.doi.org/10.1007/3-540-34416-0 |z Accès INSA CVL | |
| 997 | |0 938601 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||