Inductive inference for large scale text classification : Kernel approaches and techniques
Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the wide...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2010.
Cham : Springer Nature |
| Serier: | Studies in Computational Intelligence
255 |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Inductive Inference for Large Scale Text Classification, Texte imprimé, 9783642045325 • Inductive Inference for Large Scale Text Classification, Texte imprimé, 9783642045363 • Inductive Inference for Large Scale Text Classification, Texte imprimé, 9783642261343 |
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| 100 | 1 | |a Silva, Catarina. | |
| 245 | 1 | 0 | |a Inductive inference for large scale text classification : |b Kernel approaches and techniques |c by Catarina Silva, Bernardete Ribeiro. |
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c 2010. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 255 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Fundamentals -- Background on Text Classification -- Kernel Machines for Text Classification -- Approaches and techniques -- Enhancing SVMs for Text Classification -- Scaling RVMs for Text Classification -- Distributing Text Classification in Grid Environments -- Framework for Text Classification. | |
| 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. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques. | ||
| 700 | 1 | |a Ribeiro, Bernardete. |4 aut | |
| 776 | 0 | |t Inductive Inference for Large Scale Text Classification |b Texte imprimé |z 9783642045325 | |
| 776 | 0 | |t Inductive Inference for Large Scale Text Classification |b Texte imprimé |z 9783642045363 | |
| 776 | 0 | |t Inductive Inference for Large Scale Text Classification |b Texte imprimé |z 9783642261343 | |
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