. We applied the proposed method to real-world as well as models of complex networks. We empirically found that real …-world complex networks were embedded in a Euclidean space of relatively lower dimensions and the configuration of vertices in the … a way not only to visualize the complex networks in a Euclidean space but to characterize the complex networks in a …

machine translation. Most importantly, so far only a few metrics of complex networks have been used and therefore there is … in comparison to previous work employing complex networks. With an optimized method the Rouge score (an automatic … statistical methods based on complex networks for Brazilian Portuguese. Furthermore, the diversity metric can detect keywords with …

features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which … complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of …

, found, for example, in some models of complex networks. With minor modifications, the algorithm might also be used for …Roulette-wheel selection is a frequently used method in genetic and evolutionary algorithms or in modeling of complex … networks. Existing routines select one of N individuals using search algorithms of O(N) or O(logN) complexity. We present a …

This work proposes a method for data clustering based on complex networks theory. A data set is represented as a …

Community detection is one of the most investigated problems in the field of complex networks. Although several methods …

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the …