Automatic extraction of collocations from large corpora has been the focus of many research efforts. Most approaches concentrate on improving and combining known lexical association measures. In this paper, we describe a genetic programming approach for evolving new association measures, which is not limited to any specific language, corpus, or type of collocation. Our preliminary experimental ...

A key data preparation step in Text Mining, Term Extraction selects the terms, or collocation of words, attached to specific concepts. In this paper, the task of extracting relevant collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as relevant/irrelevant. The candidate terms are described along 13 standard statistical criteria meas...

The immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. Spatial association analysis is a typical data mining approach for discovering spatial knowledge. Associate rules are patterns of form X→Y, where pattern Y is likely to occur when pattern X occurs. One of the most famous patterns, Diapers → Beer, is a typical association rule example. Spa...

We present greedy unsymmetric collocation schemes for solving linear elliptic partial differential equations using radial basis functions. The proposed approach circumvents the ill-conditioning problem associated with the standard collocation technique and enables the efficient solution of problems requiring a large set of collocation points. Numerical studies indicate that the accuracy of gree...

This paper proposes a word sense disambiguation (WSD) method using bilingual corpus in English-Chinese machine translation system. A mathematical model is constructed to disambiguate word in terms of context phrasal collocation. A rules learning algorithm is proposed, and an application algorithm of the learned rules is also provided, which can increase the recall ratio. Finally, an analysis is...

Keywords: Volterra integro-differential equations Multistep collocation Superconvergence Stability a b s t r a c t Multistep collocation methods for Volterra integro-differential equations are derived and analyzed. They increase the order of convergence of classical one-step collocation methods, at the same computational cost. The numerical stability analysis is carried out and classes of A 0-s...

In this paper, collocation methods are used for detecting blow-up solutions of nonlinear homogeneous Volterra-Hammerstein integral equations. To do this, we introduce the concept of “blow-up collocation solution” and analyze numerically some blow-up time estimates using collocation methods in particular examples where previous results about existence and uniqueness can be applied. Finally, we d...

Abstract. A local convergence rate is established for an orthogonal collocation method based on Radau quadrature applied to an unconstrained optimal control problem. If the continuous problem has a sufficiently smooth solution and the Hamiltonian satisfies a strong convexity condition, then the discrete problem possesses a local minimizer in a neighborhood of the continuous solution, and as the...

Collocation learning is one of the important building blocks for the development of language competence. Remarkably, it is influenced by L1 and L2 congruency. The present study thus focused on the distinguishability of the computational similarity values between L2 collocates and L1 counterparts to establish the use of semantic similarity measure as a research instrument. The results showed tha...