The paper presents (i) two similarity based methods for retrieval of pictures using indices on spatial relationships; (ii) efficient algorithms for the deduction and reduction of spatial relationships, which are used for computation of similarity values; (iii) identification of a desirable property for spatial similarity functions and the construction of such a function.

This paper outlines a project to identify reliable algorithms for measuring melodic similarity by using melodies extracted from a piece of music in Theme and Variations form, for which human judgements of similarity have been gathered.

In this paper, we introduce two kinds of word similarity algorithms, SHE and RHE, to investigate the capability of WordNet in measuring verb similarity. In the absence of a standard verb set we have proposed two new verb similarity evaluation data sets.

Text similarity detection aims at measuring the degree of similarity between a pair of texts. Corpora available for similarity detection are designed to evaluate the algorithms to assess the paraphrase level among documents. In this paper we present a textual German corpus for similarity detection. The purpose of our corpus is to automatically assess the similarity between a pair of texts and t...

In this paper we present two graph-theoretic algorithms for cluster identification and demonstrate the effectiveness of their combined use. Building on the results of our previous study using sparse matrix reordering schemes to generate clusters, we modify the most promising algorithms to take advantage of similarity scores to produce orderings that nearly recover known clusters. Both algorithm...

This abstract sketches the approach and the employed means for constructing measures of melodic similarity in our software toolbox SIMILE. For different tasks related to melodic similarity different hybrid algorithms proved to be optimal. The hybrid algorithms consist of several single algorithms mostly known in the literature that are taken together in a linear combination. One special linear ...

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between  th and th objects. The performance of clustering algorithms with b...

In this paper, we investigate adaptive relevance feedback algorithms for interactive multimedia content personalization. In particular two interesting scenarios are examined. The first uses a weighted cross correlation similarity measure for ranking multimedia data. The second exploits concepts of functional analysis to model the similarity measure as a non-linear function, the type of which is...

We have already proposed a similarity-based mating scheme to recombine extreme and similar parents for evolutionary multiobjective optimization. In this paper, we examine the effect of the similarity-based mating scheme on the performance of evolutionary multiobjective optimization (EMO) algorithms. First we examine which is better between recombining similar or dissimilar parents. Next we exam...

This paper proposes an innovative instance similarity based evaluation metric that reduces the search map for clustering to be performed. An aggregate global score is calculated for each instance using the novel idea of Fibonacci series. The use of Fibonacci numbers is able to separate the instances effectively and, in hence, the intra-cluster similarity is increased and the intercluster simila...