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Mu, Jin; Stegmann, Karsten; Mayfield, Elijah; Rose, Carolyn; Fischer, Frank – International Journal of Computer-Supported Collaborative Learning, 2012
Research related to online discussions frequently faces the problem of analyzing huge corpora. Natural Language Processing (NLP) technologies may allow automating this analysis. However, the state-of-the-art in machine learning and text mining approaches yields models that do not transfer well between corpora related to different topics. Also,…
Descriptors: Semantics, Classification, Syntax, Coding
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Wagner, Joachim; Foster, Jennifer; van Genabith, Josef – CALICO Journal, 2009
A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this article, we describe a classifier which classifies English sentences as either well formed or ill formed using information gleaned from three different…
Descriptors: Sentences, Language Processing, Natural Language Processing, Grammar
Matthiessen, Christian; Kasper, Robert – 1987
Consisting of two separate papers, "Representational Issues in Systemic Functional Grammar," by Christian Matthiessen and "Systemic Grammar and Functional Unification Grammar," by Robert Kasper, this document deals with systemic aspects of natural language processing and linguistic theory and with computational applications of…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Computational Linguistics
Matthiessen, Christian – 1987
Taking the lexicogrammatical resources (i.e. the vocabulary and syntax) of English as a starting point, this report explores the demands those resources put on the design of the part of a text generation system that supports the process of lexicogrammatical expression. The first section of the report notes that a reason for using the lexicogrammar…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Computer Uses in Education