In this paper we present a new algorithm for the Person Cross Document Coreference task. We show that accurate results require a way to adapt the parameters of the similarity function – metrics and threshold – to the ontological constraints obeyed by individuals. The technique we propose dynamically changes the initial weights computed when the context is analyzed. The weight recomputation is n...

Secondly combining group theory and singularity analysis we obtained some information about the similarity solutions of the fourth order generalized Boussinesq equation GBE4. It has been shown that this equation possess a three dimensional Lie algebra of the point symmetries and the similarity reductions due to these symmetries have been obtained.

This paper investigates subsequent matching approach and feature-based classification for activity recognition using accelerometer readings. Recognition is done by similarity measure based on DTWs on each acceleration axis. Preliminary ensemble method is proposed and comparative study is executed showing better and more stable results.

We present a technique for estimating the similarity between objects such as movies or foods whose proper representation depends on human perception. Our technique combines a modest number of human similarity assessments to infer a pairwise similarity function between the objects. This similarity function captures some human notion of similarity which may be difficult or impossible to automatic...

Event counting is significant when it allows us to discover and represent implicit knowledge. We realize that a particular event happens somewhere not just by mere chance, it is unlikely to be what we call as accidental event. E.g. the number of violent attacks and terrorist acts can give the measure of the safety for a given country and can help us to predict where and/or when similar events a...

We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and parallel surfaces in this space. It further uses sequences of images to obtain more reliable clustering. Finally, since our method relies on a non-Euclidean similarity measure we introduce algebraic techniques for estimat...

Context-aware computing applications often perform an assessment of similarity between the user’s current situation and the predefined or learned situations in order to trigger appropriate adaptation rules. Because future situations are often not exactly matching with past ones (e.g., time continuously changes), the assessment of similarity between situations is not a straightforward task. This...

In this paper, we propose a novel Fourier-theoretic approach for estimating the symmetry group G of a geometric object X. Our approach takes as input a geometric similarity matrix between low-order combinations of features of X and then searches within the tree of all feature permutations to detect the sparse subset that defines the symmetry group G of X. Using the Fouriertheoretic approach, we...

This article presents a distance and angle similarity measure. The integrated similarity measure takes the strengths of both the distance and direction of measured documents into account. This article analyzes the features of the similarity measure by comparing it with the traditional distance-based similarity measure and the cosine measure, providing the iso-similarity contour, investigating t...

We suggest to define objective probabilities by similarity-weighted empirical frequencies, where more similar cases get a higher weight in the computation of frequencies. This formula is justified intuitively and axiomatically, but raises the question, which similarity function should be used? We propose to estimate the similarity function from the data, and thus obtain objective probabilities....