In this paper we present a new method of automatic collocation identification. Collocation is an important relation between words, which is widely used, among others, in information retrieval tasks. Over the last years, many methods of automatic collocation acquisition from text corpora have been proposed. The approach described in this paper differs from the others by focusing on domain colloc...

This paper describes the use of WordNet in a new technique for collocation extraction. The approach is based on restrictions on the possible substitutions for synonyms within candidate phrases. Following a general discussion of collocations and their applications, current extraction methods are briefly described. This is followed by a detailed description of the new approach and results and eva...

In this paper, we introduce a generalized Chebyshev collocation method (GCCM) based on the generalized Chebyshev polynomials for solving stiff systems. For employing a technique of the embedded Runge-Kutta method used in explicit schemes, the property of the generalized Chebyshev polynomials is used, in which the nodes for the higher degree polynomial are overlapped with those for the lower deg...

A relaxation-based algorithnl is proposed that improves the performance of a text recognition technique by propagating the influence of word collocation statistics. Word collocation refers to the likelihood that two words co-occur within a fixed distance of one another. For example, in a story about water transportation, it is highly likely that the word "river" will occur within ten words on e...

We develop an exponentially accurate fractional spectral collocation method for solving steady-state and time-dependent fractional PDEs (FPDEs). We first introduce a new family of interpolants, called fractional Lagrange interpolants, which satisfy the Kronecker delta property at collocation points. We perform such a construction following a spectral theory recently developed in [M. Zayernouri ...

We consider the Fer and the Magnus expansions for the numerical solution of the nonlinear matrix Lie-group ODE y 0 = (t; y)y; y(0) = y0; where y evolves in a matrix Lie group G and (t; y) is in the Lie algebra g. Departing from a geometrical approach, that distinguishes between those operations performed in the group and those performed in the tangent space, we construct Lie-group invariant met...