000 03218nam a22004575i 4500
001 978-3-642-22913-8
003 DE-He213
005 20140220083810.0
007 cr nn 008mamaa
008 110924s2011 gw | s |||| 0|eng d
020 _a9783642229138
_9978-3-642-22913-8
024 7 _a10.1007/978-3-642-22913-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aBiba, Marenglen.
_eeditor.
245 1 0 _aLearning Structure and Schemas from Documents
_h[electronic resource] /
_cedited by Marenglen Biba, Fatos Xhafa.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2011.
300 _aXVIII, 442p. 98 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v375
505 0 _aFrom the content: Learning Structure and Schemas from Heterogeneous Domains in Networked Systems Surveyed -- Handling Hierarchically Structured Resources Addressing Interoperability Issues in Digital Libraries -- Administrative Document Analysis and Structure -- Automatic Document Layout Analysis through Relational Machine Learning -- Dataspaces: where structure and schema meet.
520 _aThe 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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aXhafa, Fatos.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642229121
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v375
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-22913-8
912 _aZDB-2-ENG
999 _c108279
_d108279