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Titlebook: Case-Based Reasoning Research and Development; 26th International C Michael T. Cox,Peter Funk,Shahina Begum Conference proceedings 2018 Spr

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书目名称Case-Based Reasoning Research and Development
副标题26th International C
编辑Michael T. Cox,Peter Funk,Shahina Begum
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Case-Based Reasoning Research and Development; 26th International C Michael T. Cox,Peter Funk,Shahina Begum Conference proceedings 2018 Spr
描述.This book constitutes the refereed proceedings of the 26th International Conference on Case-Based Reasoning Research and Development, ICCBR 2018, held in Stockholm, Sweden, in July 2018...The 39 full papers presented in this book were carefully reviewed and selected from 77 submissions. The theme of ICCBR-2017, "The Future of CBR", was highlighted by several activities..These papers, which are included in the proceedings, address many themes related to the theory and application of case-based reasoning and its future direction. Topics included multiple papers on textual CBR and a number of cognitive and human oriented papers as well as hybrid research between CBR and machine learning..
出版日期Conference proceedings 2018
关键词activity recognition; artificial intelligence; case based reasoning; cbr; domain knowledge; Human-Compute
版次1
doihttps://doi.org/10.1007/978-3-030-01081-2
isbn_softcover978-3-030-01080-5
isbn_ebook978-3-030-01081-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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AI-VT: An Example of CBR that Generates a Variety of Solutions to the Same Problems, even if the generation of training sessions is based on analogy and must integrate the repetition of some exercises, it also must introduce some diversity and AI-VT must deal with this diversity. In this paper, we have highlighted the fact that the retaining (or capitalisation) phase of CBR is of
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Harnessing Hundreds of Millions of Cases: Case-Based Prediction at Industrial Scaleion. Handling this application required addressing how to keep LSH practical for skewed data; the resulting efficiency gains in turn enabled applying an adaptation generation strategy that previously was computationally infeasible. Experimental results show that our CBR approach achieves accuracy co
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Dynamic Detection of Radical Profiles in Social Networks Using Image Feature Descriptors and a Case-ion with confirmed radical profiles. These techniques are combined in the context of a Case-Based Reasoning framework which, together with the feedback provided by the end-user, enables a continuous monitoring of the activity of radical users and eases the discovery of new profiles with a radicaliza
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I. Shibuya,K. Uchida,M. Mochizukis, even if the generation of training sessions is based on analogy and must integrate the repetition of some exercises, it also must introduce some diversity and AI-VT must deal with this diversity. In this paper, we have highlighted the fact that the retaining (or capitalisation) phase of CBR is of
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