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Case-Based Reasoning via Comparing the Strength Order of Features
YU, Liuwen; GABBAY, Dov M.
2022In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13283 LNAI, p. 143-151
Peer reviewed
 

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Keywords :
Argumentation; Case-based reasoning; Legal reasoning; Strength of features; Computers; Case based; Casebased reasonings (CBR); New case; Relative strength; Similar case; Strength of feature; Case based reasoning
Abstract :
[en] Case-based reasoning (CBR) is broadly speaking a method of giving a verdict/decision on a new case query by comparing it with verdicts/decisions of known similar cases. Similarity of cases is determined either by best distance of the query case from the known cases and recently also using argumentation. The approach of this paper is not to rely on similarity or argumentation, but to use the entire set of known cases and their known verdicts to define the relative strength and importance of all the features involved in these cases. We then decide the verdict for the new case based on the strength of the features appearing in it.
Disciplines :
Computer science
Identifiers :
eid=2-s2.0-85140493271
Author, co-author :
YU, Liuwen  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PI VDT
GABBAY, Dov M. ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) ; King's College, London
External co-authors :
yes
Language :
English
Title :
Case-Based Reasoning via Comparing the Strength Order of Features
Publication date :
2022
Event name :
4th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2022
Event date :
9 May 2022 through 10 May 2022
Audience :
International
Journal title :
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN :
0302-9743
Publisher :
Springer Science and Business Media Deutschland GmbH
Volume :
13283 LNAI
Pages :
143-151
Peer reviewed :
Peer reviewed
European Projects :
H2020 - 814177 - LAST-JD-RIoE - Law, Science and Technology Joint Doctorate: Rights of the Internet of Everything
Funders :
Horizon 2020 Framework Programme, H2020; H2020 Marie Skłodowska-Curie Actions, MSCA: 814177
CE - Commission Européenne
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