Toward automating a personalized concordancer for data-driven language learning

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Title:	Toward automating a personalized concordancer for data-driven language learning
Authors:	衛友賢;Wible, David Scott;Chien, Feng-yi;郭經華;Kuo, Chin-hwa;Wang, C. C.
Contributors:	淡江大學英文學系淡江大學資訊工程學系
Date:	2002-07-01
Issue Date:	2010-01-07 10:32:31 (UTC+8)
Publisher:	Amsterdam: Rodopi
Abstract:	One of the most widely acknowledged barriers to the effectiveness of corpus and concordancing resources in the hands of language learners and educators is the lack of control over the examples retrieved. The purpose of this paper is to describe a novel tool, called the Lexical Difficulty Filter (LDF), which we have developed to increase this sort of control, specifically to filter concordance examples according to a flexible threshold of lexical difficulty. We also suggest refinements and extensions to the LDF for future research. What we present here constitutes one part of a larger effort that we are engaging in to provide precision and flexibility for language teachers and learners in their use of concordancing tools and large corpora.
Relation:	Language and Computers : Studies in practical linguistics, pp.147-154
Appears in Collections:	[Graduate Institute & Department of English] Chapter [Graduate Institute & Department of Computer Science and Information Engineering] Chapter

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