A dynamic adaptive framework for Case-Based Reasoning
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Bester Preis: € 49,70 (vom 24.11.2019)1
A dynamic adaptive framework for Case-Based Reasoning
~EN NW ABISBN: 9783659897870 bzw. 3659897876, vermutlich in Englisch, neu, Hörbuch.
Lieferung aus: Schweiz, Lieferzeit: 2 Tage, zzgl. Versandkosten.
To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient in size, especially in continuous domains. One of the main contributions of the work is the proposal of a Dynamic Adaptive Case Library (DACL) framework. It learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain. provides a very good approach both to improve the time efficiency and the competence in CBR systems.
To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient in size, especially in continuous domains. One of the main contributions of the work is the proposal of a Dynamic Adaptive Case Library (DACL) framework. It learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain. provides a very good approach both to improve the time efficiency and the competence in CBR systems.
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A dynamic adaptive framework for Case-Based Reasoning - Dynamic Learning and indexing the new knowledge in a Dynamic Adaptive Case Library, for static and dynamic domains
~EN PB NWISBN: 9783659897870 bzw. 3659897876, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
A dynamic adaptive framework for Case-Based Reasoning: To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient in size, especially in continuous domains. One of the main contributions of the work is the proposal of a Dynamic Adaptive Case Library (DACL) framework. It learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain. provides a very good approach both to improve the time efficiency and the competence in CBR systems. Englisch, Taschenbuch.
A dynamic adaptive framework for Case-Based Reasoning: To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient in size, especially in continuous domains. One of the main contributions of the work is the proposal of a Dynamic Adaptive Case Library (DACL) framework. It learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain. provides a very good approach both to improve the time efficiency and the competence in CBR systems. Englisch, Taschenbuch.
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A dynamic adaptive framework for Case-Based Reasoning
DE HC NWISBN: 9783659897870 bzw. 3659897876, in Deutsch, Lap Lambert Academic Publishing, gebundenes Buch, neu.
Lieferung aus: Deutschland, Versandkostenfrei innerhalb von Deutschland.
To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient in size, especially in continuous domains. One of the main contributions of the work is the proposal of a Dynamic Adaptive Case Library (DACL) framework. It learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain. provides a very good approach both to improve the time efficiency and the competence in CBR systems. Lieferzeit 1-2 Werktage.
To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient To improve or optimize all three dimensions in a CBR system at the same time is a difficult challenge because they are interrelated, and it becomes even more difficult when the CBR system is applied to a dy-namic domain or continuous domain (data stream). In this work, a dynamic adaptive framework is proposed to improve the CBR system performance coping especially with reducing the retrieval time, increasing the CBR system competence, and maintaining and adapting the Case Library to be efficient in size, especially in continuous domains. One of the main contributions of the work is the proposal of a Dynamic Adaptive Case Library (DACL) framework. It learns cases and organizes them into dynamic cluster structures. The DACL is able to adapt itself to a dynamic environment, where new clusters, meta-cases or prototype of cases, and associated indexing structures (discriminant trees, k-d trees, etc.) can be formed, updated, or even removed. DACL offers a possible solution to the management of the large amount of data generated in an unsupervised continuous domain. provides a very good approach both to improve the time efficiency and the competence in CBR systems. Lieferzeit 1-2 Werktage.
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A dynamic adaptive framework for Case-Based Reasoning
~EN NWISBN: 3659897876 bzw. 9783659897870, vermutlich in Englisch, neu.
A dynamic adaptive framework for Case-Based Reasoning ab 64.9 EURO Dynamic Learning and indexing the new knowledge in a Dynamic Adaptive Case Library for static and dynamic domains.
5
A dynamic adaptive framework for Case-Based Reasoning
~EN PB NWISBN: 3659897876 bzw. 9783659897870, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
A dynamic adaptive framework for Case-Based Reasoning ab 64.9 € als Taschenbuch: Dynamic Learning and indexing the new knowledge in a Dynamic Adaptive Case Library for static and dynamic domains. Aus dem Bereich: Bücher, English, International, Gebundene Ausgaben,.
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A dynamic adaptive framework for Case-Based Reasoning (2016)
DE PB NW RPISBN: 9783659897870 bzw. 3659897876, in Deutsch, LAP Lambert Academic Publishing Jul 2016, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Neuware - 208 pp. Englisch.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Neuware - 208 pp. Englisch.
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A dynamic adaptive framework for Case-Based Reasoning: Dynamic Learning and indexing the new knowledge in a Dynamic Adaptive Case Library, for static and dynamic domains (2016)
DE PB NW RPISBN: 9783659897870 bzw. 3659897876, in Deutsch, Lap Lambert Academic Publishing, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
This item is printed on demand for shipment within 3 working days.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
This item is printed on demand for shipment within 3 working days.
8
A dynamic adaptive framework for Case-Based Reasoning
DE NWISBN: 9783659897870 bzw. 3659897876, in Deutsch, neu.
Lieferung aus: Deutschland, Versandkosten, 3659897876.
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Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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