Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Abstract. In both research fields, Case-Based Reasoning and Reinforcement Learning, the system under consideration gains its expertise from experience. Utilizing this fundamental c...
Abstract. Evaluation criteria for conversational CBR (CCBR) systems are important to guide development and tuning of new methods, and to enable practitioners to make informed decis...
This paper describes the development of the generic collaboration support architecture CAKE incorporating case-based reasoning (CBR). CAKE provides unified access to knowledge avai...
Abstract. We present a CBR approach to musical playlist recommendation. A good playlist is not merely a bunch of songs, but a selected collection of songs, arranged in a meaningful...
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
The success of a company more and more depends on its ability to flexibly and quickly react to changes. Combining process management techniques and conversational case-based reason...
Product recommender systems are a popular application and research field of CBR for several years now. However, almost all CBRbased recommender systems are not case-based in the or...