Context-dependent similarity
نویسنده
چکیده
Numerical similarity measures are used to de scribe the relative ranks of the similarity of ob jects or cases in many artificial intelligent systems. These measures are usually absolute and context independent. On the other hand, humans perceive context-dependent similarity. That is, the ranking of similarity between pairs of objects is varying under a changing context. We consider this problem as the construction of numerical formulas that satisfy cer tain axioms and criteria. An entropy-related formula is proposed and its implementation in a changing environment is considered. A demonstration of this formula on a well-known context-dependent similar ity assessment is given.
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