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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams - Brossura
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The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data.
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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. Codice articolo 487888301
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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
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Karlsruher Institut Für Technologie Jul 2021, 2021
ISBN 10: 3731510766
ISBN 13: 9783731510765
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data. 236 pp. Englisch. Codice articolo 9783731510765
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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
Editore:
Karlsruher Institut Für Technologie, 2021
ISBN 10: 3731510766
ISBN 13: 9783731510765
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data. Codice articolo 9783731510765
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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
ISBN 10: 3731510766
ISBN 13: 9783731510765
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data.Books on Demand GmbH, Überseering 33, 22297 Hamburg 236 pp. Englisch. Codice articolo 9783731510765
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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
Editore:
Karlsruher Institut für Technologie, 2021
ISBN 10: 3731510766
ISBN 13: 9783731510765
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams | Matthias T. Frank | Taschenbuch | Englisch | 2021 | Karlsruher Institut für Technologie | EAN 9783731510765 | Verantwortliche Person für die EU: KIT Scientific Publishing, Straße am Forum 2, 76131 Karlsruhe, info[at]ksp[dot]kit[dot]edu | Anbieter: preigu. Codice articolo 120350447
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