Abstract Inspired by the notion of action convergence in graph limit theory, we introduce a measure-theoretic representation matrices, and use it to define new pseudo-metric on space matrices. Moreover, show that such is metric subspace adjacency or Laplacian matrices for graphs. Hence, particular, obtain isomorphism classes Additionally, study how some properties graphs translate this measure ...

We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the si...

Designing a general algorithm for interest matching is a major challenge in building online community and agent-based communication networks. This paper presents an information theoretic concept-matching approach to measure degrees of similarity among users. Kullback-Leiber distance is used as a measure of similarity on users represented by concept hierarchy. Preliminary sensitivity analysis sh...

This paper shows that the common task of interest region matching using local descriptors can be improved using a new similarity measure. The similarity measure is motivated by the information theoretic image alignment that maximize mutual information between images. A property of the mutual information metric is that it does not only depend on how similar the signals are but also how complex t...

In this paper, we present a revised similarity measure based onChen-and-Chen's similarity measure for fuzzy risk analysis. The revisedsimilarity measure uses the corrected formulae to calculate the centre ofgravity points, therefore it is more  effective than the Chen-and-Chen'smethod. The revised similarity measure can overcome the drawbacks of theexisting methods. We have also proposed a new ...