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Using typicality theory to select the best match
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/2049
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| Title: | Using typicality theory to select the best match |
| Authors: | Weber, Rosina O.
Barcia, Ricardo Miranda
Martins, Alejandro
Pacheco, Roberto |
| Issue Date: | 1996 |
| Publisher: | Springer Verlag |
| Citation: | Paper presented at The 3rd European Workshop on Case-Based Reasoning, EWCBR-96: pp. 445-459. |
| Abstract: | This paper focuses on the problem of choosing the best match among a set of
retrieved cases. The Select step is subtask of case retrieval that produces the case that
suggests the solution for the input case. There are many different ways to accomplish this
task and we propose an automatic means for it. Following the original motivation of
paralleling the human similarity heuristic we argue that the selection of the best match is
performed by humans choosing the solution that best represents the set of candidate solutions
retrieved. The solution that best represent a given data set is the “most typical” solution.
Therefore, we describe an application in a Case-Based Reasoning system using the Theory of
Typicality to calculate the Most Typical Value of a given set to automatically perform the
Select task. An example illustrates the application. |
| URI: | http://hdl.handle.net/1860/2049 |
| Appears in Collections: | Faculty Research and Publications (IST)
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