This article shows an application of the QARLA evaluation framework on DUC-2004 (tasks 2 and 5). The QARLA framework allows to evaluate summaries with regard to different features. Second, it allows to combine and meta-evaluate different similarity metrics, giving more weigh to metrics which characterize models (manual summaries) regarding automatic summaries.

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The comparison of manually annotated medical images can be done using the comparison of keywords in a lexical way or using the existing medical thesauri to calculate semantic similarity. In this paper, first we introduce the KWSim measure, a fully automated technique of measuring semantic similarity by mapping concepts(keywords) to different medical thesauri and examining the “is-a” relation ty...

A successful application of Artificial Immune Systems to the problem of recommending films to new users of a film database is used as the inspiration for an attempt to apply similar techniques to the problem of recommending web sites. Similarities and differences in the two situations are discussed as well as other approaches to recommendation problems such as collaborative filtering. The parti...

This paper presents a new similarity measure to be used for general tasks including supervised learning, which is represented by the K-nearest neighbor classifier (KNN). The proposed similarity measure is invariant to large differences in some dimensions in the feature space. The proposed metric is proved mathematically to be a metric. To test its viability for different applications, the KNN u...

We study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. Our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributi...

We address the problem of musical sequence comparison for melodic similarity. Starting with a very simple similarity measure, we improve it step-by-step to finally obtain an acceptable measure. While the measure is still simple and has only two tuning parameters, it is better than that proposed by Mongeau and Sankoff (1990) in the sense that it can distinguish variations on a particular theme f...