000 03916nam a22005055i 4500
001 978-3-642-16518-4
003 DE-He213
005 20140220083749.0
007 cr nn 008mamaa
008 110211s2011 gw | s |||| 0|eng d
020 _a9783642165184
_9978-3-642-16518-4
024 7 _a10.1007/978-3-642-16518-4
_2doi
050 4 _aQA76.9.D3
072 7 _aUN
_2bicssc
072 7 _aUMT
_2bicssc
072 7 _aCOM021000
_2bisacsh
082 0 4 _a005.74
_223
100 1 _aBellahsene, Zohra.
_eeditor.
245 1 0 _aSchema Matching and Mapping
_h[electronic resource] /
_cedited by Zohra Bellahsene, Angela Bonifati, Erhard Rahm.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2011.
300 _aXII, 320 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aData-Centric Systems and Applications
505 0 _aPart I: Large-scale and knowledge-driven schema matching. 1. Towards large-scale schema and ontology matching. 2. Interactive techniques to support ontology matching. 3. Enhancing the capabilities of attribute cor­respondences. 4. Uncertainty in data integration and dataspace support platforms -- Part II: Quality-driven schema mapping and evolution. 5. Discovery and correctness of schema mapping transformations. 6. Recent advances in schema and ontology evolution. 7. Schema mapping evolution through composition and inversion. 8. Mapping-based merg­ing of schemas -- Part III: Evaluating and tuning of matching tasks. 9. On evaluating schema matching and mapping. 10. Tuning for schema matching.
520 _aRequiring heterogeneous information systems to cooperate and communicate has now become crucial, especially in application areas like e-business, Web-based mash-ups and the life sciences. Such cooperating systems have to automatically and efficiently match, exchange, transform and integrate large data sets from different sources and of different structure in order to enable seamless data exchange and transformation. The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks. The authors describe the state of the art by discussing the latest achievements such as more effective methods for matching data, mapping transformation verification, adaptation to the context and size of the matching and mapping tasks, mapping-driven schema evolution and merging, and mapping evaluation and tuning. The overall result is a coherent, comprehensive picture of the field. With this book, the editors introduce graduate students and advanced professionals to this exciting field. For researchers, they provide an up-to-date source of reference about schema and ontology matching, schema and ontology evolution, and schema merging.
650 0 _aComputer science.
650 0 _aDatabase management.
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aDatabase Management.
650 2 4 _aMathematical Logic and Formal Languages.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aBonifati, Angela.
_eeditor.
700 1 _aRahm, Erhard.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642165177
830 0 _aData-Centric Systems and Applications
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-16518-4
912 _aZDB-2-SCS
999 _c107162
_d107162