Learning Structure and Schemas from Documents

The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to th...

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Détails bibliographiques
Auteur principal: Biba, Marenglen
Autres auteurs: Xhafa, Fatos (Éditeur intellectuel, Directeur de la publication), Biba, Marenglen, 19..- (Directeur de la publication)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:1st ed. 2011.
Collection:Studies in Computational Intelligence 375
Accès en ligne:Accès sur la plateforme de l'éditeur
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Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Learning Structure and Schemas from Documents, Texte imprimé, 9783642229121
• Learning Structure and Schemas from Documents, Texte imprimé, 9783642229121
• Learning Structure and Schemas from Documents, Texte imprimé, 9783642229145
• Learning Structure and Schemas from Documents, Texte imprimé, 9783662506714
Description
Résumé:The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to the extremely large volumes of documents and to their unstructured form, most of the research efforts in this direction are dedicated to automatically infer structure and schemas that can help to better organize huge collections of documents and data.   This book covers the latest advances in structure inference in heterogeneous collections of documents and data. The book brings a comprehensive view of the state-of-the-art in the area, presents some lessons learned and identifies new research issues, challenges and opportunities for further research agenda and developments.  The selected chapters cover a broad range of research issues, from theoretical approaches to case studies and best practices in the field.   Researcher, software developers, practitioners and students interested in the field of learning structure and schemas from documents will find the comprehensive coverage of this book useful for their research, academic, development and practice activity
Description:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783642229138
ISSN:1860-9503
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Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017