On combining knowledge-engineered and network-extracted features for retrieval
Z Wilkerson, D Leake, DJ Crandall - Case-Based Reasoning Research …, 2021 - Springer
The quality of case retrieval in case-based reasoning (CBR) systems depends on assigning
appropriate case indices. Defining feature vocabularies for indexing is an important …
appropriate case indices. Defining feature vocabularies for indexing is an important …
Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach
High-quality indices are essential for accurate retrieval in case-based reasoning. However,
in some domains, indexing knowledge may be incomplete, unavailable, or unfeasible to …
in some domains, indexing knowledge may be incomplete, unavailable, or unfeasible to …
Extracting case indices from convolutional neural networks: a comparative study
D Leake, Z Wilkerson, D Crandall - International Conference on Case …, 2022 - Springer
Abstract Machine learning for extracting case features can provide great benefit over feature
engineering for retrieval in poorly understood or hard to characterize domains. The …
engineering for retrieval in poorly understood or hard to characterize domains. The …
Enhancing Case-Based Reasoning with Neural Networks
D Leake, Z Wilkerson, X Ye… - Compendium of …, 2023 - ebooks.iospress.nl
Integrations of case-based reasoning (CBR) with neural approaches are appealing because
of their complimentary characteristics. This chapter presents research on neuro-symbolic …
of their complimentary characteristics. This chapter presents research on neuro-symbolic …
Harmonizing case retrieval and adaptation with alternating optimization
D Leake, X Ye - Case-Based Reasoning Research and Development …, 2021 - Springer
Case-based reasoning (CBR) research has developed numerous methods for learning to
improve case retrieval and adaptation knowledge. Learning for each type of knowledge is …
improve case retrieval and adaptation knowledge. Learning for each type of knowledge is …
[PDF][PDF] Recent themes in case-based reasoning and knowledge discovery
Case-based reasoning (CBR) systems have tight connections with machine learning and
knowledge discovery and often incorporate diverse knowledge discovery functionalities and …
knowledge discovery and often incorporate diverse knowledge discovery functionalities and …
Cases without borders: automating knowledge acquisition approach using deep autoencoders and siamese networks in case-based reasoning
K Amin - 2019 IEEE 31st International Conference on Tools …, 2019 - ieeexplore.ieee.org
Finding an ideal text case-base representation for a new domain is important for a CBR [1]
system. To do this, the choice of an ideal representation is guided by the domain …
system. To do this, the choice of an ideal representation is guided by the domain …
Learning feature taxonomies for case indexing
KM Gupta, DW Aha, P Moore - European Conference on Case-Based …, 2004 - Springer
Taxonomic case retrieval systems significantly outperform standard conversational case
retrieval systems. However, their feature taxonomies, which are the principal reason for their …
retrieval systems. However, their feature taxonomies, which are the principal reason for their …
A retrieval strategy for case-based reasoning using similarity and association knowledge
YB Kang, S Krishnaswamy… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
Retrieval is a key phase in case-based reasoning (CBR), since it lays the foundation for the
overall effectiveness of CBR systems. Its aim is to retrieve useful cases that can be used to …
overall effectiveness of CBR systems. Its aim is to retrieve useful cases that can be used to …
Maintaining case knowledge vocabulary using a new Evidential Attribute Clustering method
Maintaining the vocabulary of case knowledge within Case Based Reasoning (CBR)
presents a crucial task to ensure a high-quality problem-solving and to improve retrieval …
presents a crucial task to ensure a high-quality problem-solving and to improve retrieval …