How to reuse or adapt past solutions to new problems is one of the least understood problems in case-based reasoning. In this paper we will focus on the problem of how to combine s...
Abstract. Case-Based Reasoning (CBR) solves problems by reusing past problemsolving experiences maintained in a casebase. The key CBR knowledge container therefore is its casebase....
Abstract. Acquiring adaptation knowledge for case-based reasoning systems is a challenging problem. Such knowledge is typically elicited from domain experts or extracted from the c...
Product recommendation systems are now a key part of many e-commerce services and have proven to be a successful way to help users navigate complex product spaces. In this paper, w...
The need for automated text evaluation is common to several AI disciplines. In this work, we explore the use of Machine Translation (MT) evaluation metrics for Textual Case Based R...
Ibrahim Adeyanju, Nirmalie Wiratunga, Robert Lothi...
This paper addresses the issue of adapting cases represented by plain text with the help of formal concept analysis and natural language processing technologies. The actual cases r...
Valmi Dufour-Lussier, Jean Lieber, Emmanuel Nauer,...
Abstract. This paper presents an algorithm of adaptation for a case-based reasoning system with cases and domain knowledge represented in the expressive description logic ALC. The ...
In previous papers we have presented our autonomous poker playing agent (SARTRE) that uses a memory-based approach to create a betting strategy for two-player, limit Texas Hold’e...