Foundations of computational intelligence. Volume 6, Data mining
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully...
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| Outros Autores: | , , , , |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edição: | 1st ed. 2009. |
| coleção: | Studies in Computational Intelligence
206 |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Foundations of computational intelligence, Volume 6, Data mining, Ajith Abraham, Aboul-Ella Hassanien, André Ponce de Leon F. de Carvalho [et al.], Berlin, Springer, 2009, Studies in computational intelligence, 978-3-642-01090-3 • Foundations of Computational Intelligence, Texte imprimé, 9783642010927 • Foundations of Computational Intelligence, Texte imprimé, 9783642101670 • Foundations of computational intelligence, Volume 6, Data mining, Ajith Abraham, Aboul-Ella Hassanien, André Ponce de Leon F. de Carvalho [et al.], Berlin, Springer, 2009, Studies in computational intelligence, 978-3-642-01090-3 |
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| 245 | 0 | 0 | |a Foundations of computational intelligence. |n Volume 6, |p Data mining |c edited by Janusz Kacprzyk, Ajith Abraham, Aboul-Ella Hassanien, André Ponce Leon F. de Carvalho, Václav Snášel. |
| 250 | |a 1st ed. 2009. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 206 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Data Click Streams and Temporal Data Mining Mining and Analysis of Clickstream Patterns An Overview on Mining Data Streams Data Stream Mining Using Granularity-Based Approach Time Granularity in Temporal Data Mining Mining User Preference Model from Utterances Text and Rule Mining Text Summarization: An Old Challenge and New Approaches From Faceted Classification to Knowledge Discovery of Semi-structured Text Records Multi-value Association Patterns and Data Mining Clustering Time Series Data: An Evolutionary Approach Support Vector Clustering: From Local Constraint to Global Stability New Algorithms for Generation Decision Trees Ant-Miner and Its Modifications Data Mining Applications Automated Incremental Building of Weighted Semantic Web Repository A Data Mining Approach for Adaptive Path Planning on Large Road Networks Linear Models for Visual Data Mining in Medical Images A Framework for Composing Knowledge Discovery Workflows in Grids Distributed Data Clustering: A Comparative Analysis | |
| 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 Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; artificial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are applied to Data Mining problems. Computational tools or solutions based on intelligent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for Data Mining | ||
| 700 | 1 | |a Kacprzyk, Janusz, |d 1947- |4 pbd | |
| 700 | 1 | |a Carvalho, André Carlos Ponce de Leon Ferreira, |d 19..- |4 pbd | |
| 700 | 1 | |a Hassanien, Aboul Ella, |d 1964- |4 pbd | |
| 700 | 1 | |a Snášel, Václav. |4 pbd | |
| 700 | 1 | |a Abraham, Ajith, |d 1968- |4 pbd | |
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| 776 | 0 | |t Foundations of Computational Intelligence |b Texte imprimé |z 9783642010927 | |
| 776 | 0 | |t Foundations of Computational Intelligence |b Texte imprimé |z 9783642101670 | |
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