This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...
There are case-based recommender systems that generate personalized recommendations for users exploiting the knowledge contained in past recommendation cases. These systems assume ...
Conventional approaches to similarity search and case-based retrieval, such as nearest neighbor search, require the specification of a global similarity measure which is typically ...
"Similar problems have similar solutions" is a basic tenet of case-based inference. However this is not satisfied for CBR systems where the task is to achieve original so...
The domain of cookery has been of interest for Case-Based Reasoning (CBR) research for many years since the CHEF case-based planning system in the mid 1980s. This paper returns to ...
Qian Zhang, Rong Hu, Brian Mac Namee, Sarah Jane D...
The use of computational methods is fundamental in cancer research. One of the possibilities is the use of Artificial Intelligence techniques. Several of these techniques have been...
In this paper we present ColibriCook: a CBR system for ontology-based cooking recipe retrieval and adaptation. The system's purpose is to participate in the 1st Computer Cooki...
Textual-case based reasoning (TCBR) systems where the problem and solution are in free text form are hard to evaluate. In the absence of class information, domain experts are neede...
M. A. Raghunandan, Nirmalie Wiratunga, Sutanu Chak...
We present an approach to visualize textual case bases by "stacking" similar cases and features close to each other in an image derived from the casefeature matrix. We pr...
Abstract. This paper presents a case-based approach to decision support for diabetes management in patients with Type 1 diabetes on insulin pump therapy. To avoid serious disease c...