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Item Details
Title: LEARNING STRUCTURE AND SCHEMAS FROM DOCUMENTS
By: Marenglen Biba (Editor), Fatos Xhafa (Editor)
Format: Hardback

List price: £159.99


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ISBN 10: 3642229123
ISBN 13: 9783642229121
Publisher: SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG
Pub. date: 3 September, 2011
Edition: 2011 ed.
Series: Studies in Computational Intelligence 375
Pages: 441
Description: This book covers the latest advances in structure inference in heterogeneous collections of documents and data, offering a comprehensive view of the state of the art, and identifying challenges and opportunities for further research agenda and developments.
Synopsis: 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.
Illustrations: biography
Publication: Germany
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Returns: Returnable
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