An Overview and Comparison of Case-Based Reasoning Frameworks

被引：7

作者：

Schultheis, Alexander ^{[1
]}

Zeyen, Christian ^{[1
]}

Bergmann, Ralph ^{[1
,2
]}

机构：

[1] Univ Trier, German Res Ctr Artificial Intelligence DFKI Branc, Behringstr 21, D-54296 Trier, Germany

[2] Univ Trier, Business Informat Syst 2, D-54286 Trier, Germany

来源：

CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2023 | 2023年 / 14141卷

关键词：

Case-Based Reasoning; CBR Framework; CBR Applications; CloodCBR; eXiT*CBR; jColibri; myCBR; ProCAKE; RETRIEVAL; SYSTEMS; MEMORY; TOOL;

D O I：

10.1007/978-3-031-40177-0_21

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Case-Based Reasoning (CBR) is a methodology with many applications in industrial and scientific domains. Over the past decades, various frameworks have been developed to facilitate the development of CBR applications. For practitioners and researchers, it is challenging to overview the landscape of existing frameworks with their specific scope and features. This makes it difficult to choose the most suitable framework for specific requirements. To address this issue, this work provides an overview and comparison of CBR frameworks, focusing on five recent, open-source CBR frameworks: CloodCBR, eXiT*CBR, jColibri, myCBR, and ProCAKE. They are compared by supported CBR types, knowledge containers, CBR phases, interfaces, and special features.

引用

页码：327 / 343

页数：17

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