schema matching mapping (36 résultats)

Etat : New. In.

Etat : New.

Taschenbuch. Etat : Neu. Neuware -Revision with unchanged content. The book focuses on Schema Matching, the task of (semi-)automatically identifying semantic correspondences between elements of metadata structures, such as, database schemas, ontologies, and XML message formats. It is of key importance for interoperability and data integration in numerous applications, such as data warehousing, integration of web-sources, message mapping in E-business, and ontology alignment on the Semantic Web. However, in today's systems, schema matching is still manual; a time-consuming, tedious, and error-prone process, which becomes increasingly impractical considering the high complexity and number of schemas and data sources to be dealt with. In this book, the author Do Hong Hai describes the architecture, functionality, and evaluation of the schema matching system COMA++ (Combining Matchers), which was developed by himself in his Ph.d thesis. COMA++ represents a generic and customizable system for semi-automatic schema matching, which can combine different match algorithms in a flexible way. In comprehensive evaluations using large real-world schemas and ontologies, COMA++ has shown high quality as compared to the state of the art, proving its practicability for different domains. In addition, the book describes a new data integration approach, GenMapper (Generic Mapper), which utilizes instance-level correspondences between objects of data sources.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 228 pp. Englisch.

Einband - flex.(Paperback). Etat : New.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Requiring 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.

Etat : New. In.

Buch. Etat : Neu. Neuware -Requiring 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 332 pp. Englisch.

Etat : New. In.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Requiring 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.

Etat : New.

Etat : New.

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Etat : New. pp. 334.

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Etat : New. pp. 334 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Etat : New. pp. 334.

Etat : New. pp. 334.

Hardcover. Etat : Brand New. 326 pages. 9.75x6.50x0.75 inches. In Stock.

Etat : New.

Paperback. Etat : Like New. Like New. book.

Etat : New.

Etat : As New. Unread book in perfect condition.

Hardcover. Etat : Like New. Like New. book.

Paperback. Etat : Like New. Like New. book.

Etat : As New. Unread book in perfect condition.

Etat : Usado - bueno.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hong Hai DoDo Hong Hai attended school in Hanoi, Vietnam. Diploma in Computer Science (1998) and an M.A. in German Language and Literature Studies (1999) from University of Leipzig, Germany. In 2006 he finished his Ph.d. thesis on S.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Revision with unchanged content. The book focuses on Schema Matching, the task of (semi-)automatically identifying semantic correspondences between elements of metadata structures, such as, database schemas, ontologies, and XML message formats. It is of key importance for interoperability and data integration in numerous applications, such as data warehousing, integration of web-sources, message mapping in E-business, and ontology alignment on the Semantic Web. However, in today's systems, schema matching is still manual; a time-consuming, tedious, and error-prone process, which becomes increasingly impractical considering the high complexity and number of schemas and data sources to be dealt with. In this book, the author Do Hong Hai describes the architecture, functionality, and evaluation of the schema matching system COMA++ (Combining Matchers), which was developed by himself in his Ph.d thesis. COMA++ represents a generic and customizable system for semi-automatic schema matching, which can combine different match algorithms in a flexible way. In comprehensive evaluations using large real-world schemas and ontologies, COMA++ has shown high quality as compared to the state of the art, proving its practicability for different domains. In addition, the book describes a new data integration approach, GenMapper (Generic Mapper), which utilizes instance-level correspondences between objects of data sources.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Revision with unchanged content. The book focuses on Schema Matching, the task of (semi-)automatically identifying semantic correspondences between elements of metadata structures, such as, database schemas, ontologies, and XML message formats. It is of key importance for interoperability and data integration in numerous applications, such as data warehousing, integration of web-sources, message mapping in E-business, and ontology alignment on the Semantic Web. However, in today's systems, schema matching is still manual; a time-consuming, tedious, and error-prone process, which becomes increasingly impractical considering the high complexity and number of schemas and data sources to be dealt with. In this book, the author Do Hong Hai describes the architecture, functionality, and evaluation of the schema matching system COMA++ (Combining Matchers), which was developed by himself in his Ph.d thesis. COMA++ represents a generic and customizable system for semi-automatic schema matching, which can combine different match algorithms in a flexible way. In comprehensive evaluations using large real-world schemas and ontologies, COMA++ has shown high quality as compared to the state of the art, proving its practicability for different domains. In addition, the book describes a new data integration approach, GenMapper (Generic Mapper), which utilizes instance-level correspondences between objects of data sources. 228 pp. Englisch.

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive survey of current and past research on schema matching and mappingUp-to-date source of reference about schema and ontology evolution and schema mergingScholarly chapters enabling a learning experience to both experts .