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Studies in Computational Intelligence

Learning Structure and Schemas from Documents

Editors: Biba, Marenglen, Xhafa, Fatos (Eds.)

  • Presents State-Of-The-Art Methods for Structure Learning and Schema
  • Inference Case Studies and Best Practices from Real Large Scale Digital Libraries, Repositories and Corpora
  • Written by Leading Experts in the Field
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eBook $189.00
price for USA (gross)
  • ISBN 978-3-642-22913-8
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  • Immediate eBook download after purchase
Hardcover $239.00
price for USA
  • ISBN 978-3-642-22912-1
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  • Usually dispatched within 3 to 5 business days.
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About this book

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.

Table of contents (19 chapters)

  • Learning Structure and Schemas from Heterogeneous Domains in Networked Systems Surveyed

    Biba, Marenglen (et al.)

    Pages 1-16

  • Handling Hierarchically Structured Resources Addressing Interoperability Issues in Digital Libraries

    Agosti, Maristella (et al.)

    Pages 17-49

  • Administrative Document Analysis and Structure

    Belaïd, Abdel (et al.)

    Pages 51-71

  • Automatic Document Layout Analysis through Relational Machine Learning

    Ferilli, Stefano (et al.)

    Pages 73-96

  • Dataspaces: Where Structure and Schema Meet

    Atzori, Maurizio (et al.)

    Pages 97-119

Buy this book

eBook $189.00
price for USA (gross)
  • ISBN 978-3-642-22913-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $239.00
price for USA
  • ISBN 978-3-642-22912-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Learning Structure and Schemas from Documents
Editors
  • Marenglen Biba
  • Fatos Xhafa
Series Title
Studies in Computational Intelligence
Series Volume
375
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
The Editor(s) (if applicable) and The Author(s) 2018
eBook ISBN
978-3-642-22913-8
DOI
10.1007/978-3-642-22913-8
Hardcover ISBN
978-3-642-22912-1
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XVIII, 441
Topics