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A dynamic adaptive framework for Case-Based Reasoning

Name: A dynamic adaptive framework for Case-Based Reasoning
Brand: LAP Lambert Academic Publishing
SKU: 9783659897870
Price: 237.6 PLN
Availability: InStock

Dynamic Learning and indexing the new knowledge in a Dynamic Adaptive Case Library, for static and dynamic domains

Autor: Fernando Orduña-Cabrera

Język:

Oprawa: Miękka

Wydawca: LAP Lambert Academic Publishing

Dostępność: Dostępna u dostawcy

Wysyłamy za 5-8 dni

237.60 zł

To improve or optimize all three dimensions in a CBR system at the same time is a difficult challeng...

Informacje o książce

Autor

Fernando Orduña-Cabrera

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2016

strony

208

EAN

9783659897870

Enbook ID

13516139

Wydawca

LAP Lambert Academic Publishing

Waga

326

Wymiary

150 x 220 x 12

Pełny opis

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.