Explaining similarity in CBR
نویسندگان
چکیده
A desired capability of automatic problem solvers is to explain their results. Such explanations should justify that the solution proposed by the problem solver arises from the known domain knowledge. In this paper we discuss how the explanations can be used in CBR methods in order to justify the results in classification tasks and also for solving new problems.
منابع مشابه
Using Symbolic Similarity to Explain Case-based Reasoning in Classification Tasks
The explanation of the results is a key point of automatic problem solvers. CBR systems solve a new problem by assessing its similarity with already solved cases and they commonly show the user the set of cases that have been assessed as the most similar to the new problem. Using the notion of symbolic similarity, our proposal is to show the user a symbolic description that makes explicit what ...
متن کاملA similarity-based theory of CBR-II A similarity-based Theory of Case-based Reasoning-II
This work is the second part of a general similarity-based theory of case-based reasoning (CBR), which moves CBR towards a firm theoretical foundation based on similarity-based reasoning. This paper will first examine abductive CBR and deductive CBR and propose a knowledge-based model for integrating abductive CBR and deductive CBR. It then proposes similarity-based models for rule-based and fu...
متن کاملAbductive case-based reasoning
This article will introduce abductive case-based reasoning (CBR) and attempt to show that abductive CBR and deductive CBR can be integrated in clinical process and problem solving. Then it provides a unified formalization for integration of abduction, abductive CBR, deduction and deductive CBR. This article also investigates abductive case retrieval and deductive case retrieval using similarity...
متن کاملCombining Strict Matching and Similarity Assessment for Retrieving Appropriate Cases Efficiently
It is essential for case-based reasoning (CBR) systems to access trnly relevant cases efficiently. Similarity assessment adopted by many CBR systems needs performance improvement, especially if the case library of a CBR system consists of a database in the target domain which is not equipped with suitable indexing for the CBR system. In consideration of this problem, we are exploring use of str...
متن کاملUsing Reinforcement Learning for Similarity Assessment in Case-Based Systems
be a problem when applying CBR to weak-theoretic domains.1 The knowledge elicitation bottleneck—the inability to precisely encode the knowledge used by human experts—is a concern in many knowledge-based applications. Although researchers cite this bottleneck as a justification for CBR techniques,2 use of domain knowledge in indexing means that CBR techniques are not immune to it. We’ve develope...
متن کامل