Corpus linguistics and naive discriminative learning

Corpus linguistics and naive discriminative learning

Three classifiers from machine learning (the generalized linear mixed model, memory based learning, and support vector machines) are compared with a naive discriminative learning classifier, derived from basic principles of error-driven learning characterizing animal and human learning. Tested on the dative alternation in English, using the Switchboard data from (Bresnan, Cueni, Nikitina, & Baa...

Lexicography and Corpus Linguistics

Corpus linguistics and second / foreign language learning : exploring multiple paths

The aim of this article is twofold: first, to briefly assess the influence that corpus linguistic research has had on second/foreign language learning so far, and second, to suggest future directions for a more coherent and well thought out integration of corpora in instructed settings. In section 1, the influence of native and learner corpus research on second/foreign language learning will be...

Corpus Linguistics: Quantitative Methods

p. 1, par. 2: Until relatively recently, however, words and syntactic patterns, or constructions, were treated on a par not only theoretically, but also empirically. → It is only since recently, however, that words and syntactic patterns, or constructions, are treated on a par not only theoretically, but also empirically. p. 1, first bullet: how much does give prefer to occur in the ditransitiv...

Machine Translation - Corpus Linguistics

Due to the importance of communication between two or more people, companies, or even nations, the need for good translators has long been obvious around the world, and since humans are faulty, it is not surprising that many attempts to automate the process of translation have been made throughout history. This is called machine translation. Corpus linguistics, a branch of the machine translati...