Schema matching mapping based data von hong (3 Ergebnisse)
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 66,50
EUR 13,99 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In.
- Softcover
Anbieter: moluna, Greven, Deutschlandmoluna
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 71,35
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: Mehr als 20 verfügbar
Einband - flex.(Paperback). Zustand: New.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 86,69
EUR 62,21 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - 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 app…lications, 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.
