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Fuzzy Similarity Measures for Signal Pattern Classification - Youssif Purdy Ececs (Correct)
....that, in this measure the distance is measured between the truth values of the important feature existence predicates. Fuzzy Feature Contrast Similarity Measure This model has been developed in [5] in the context of Visual Information Retrieval systems, following Tversky s feature contrast model [7]. Tversky s model used a relation that compares the sets of features possessed by any two patterns to compute their similarity. Let a and b be two patterns where A and B are the sets of features possessed by each of them respectively. The Tversky similarity measure is defined as ....
A. Tversky, "Features of Similarity", Psychological Review, vol. 84, no. 4, pages 327-352, 1977.
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....C AA will take a high value because the probability of matches between S x and S y will be highest for identical pairs of patterns, it will not necessarily obtain the same value for all patterns. However, the value of C AA will always be greater than C AB provided M is large enough. Tversky [26] showed that measures of similarity that conform to human perception do not satisfy the usual properties of a metric, such as the triangular inequality. He proposed a feature contrast model relevant to human perception, but still required a set of pre specified features for its definition. The ....
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A. Tversky, "Features of Similarity", Psychological Review, pp.327-352, Vol. 84, No. 4, July 1977.
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