Learning Structure and Schemas from Documents

Name: Learning Structure and Schemas from Documents
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642229121
Price: 62139 HUF
Availability: InStock

Szerző: Marenglen Biba, Fatos Xhafa

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Elérhetőség: Beszállítói készleten alacsony példányszámban

Küldés 11-15 napon belül

62 139 Ft

The rapidly growing volume of available digital documents of various formats and the possibility to...

Információk a könyvről

Szerző

Marenglen Biba, Fatos Xhafa

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2011

oldal

441

EAN

9783642229121

ISBN

3642229123

Enbook ID

01658543

Kiadó

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Súly

1810

Méretek

167 x 242 x 40

Teljes leírás

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.

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Learning Structure and Schemas from Documents

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