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Semi-automatic selection of best corpus examples for Swedish: Initial algorithm evaluation.

Conference paper
Authors Elena Volodina
Richard Johansson
Sofie Johansson Kokkinakis
Published in Proceedings of the SLTC 2012 workshop on NLP for CALL, Lund, 25th October, 2012.
Issue 080
Pages 59-70
ISSN 1650-3740
Publication year 2012
Published at Department of Swedish
Pages 59-70
Language en
Keywords language technology, corpus linguistics, lexicography, intelligent computer-assisted language learning, ICALL, corpus example selection/ranking
Subject categories Language Technology (Computational Linguistics), Linguistics


The study presented here describes the results of the initial evaluation of two sorting approaches to automatic ranking of corpus examples for Swedish. Representatives from two potential target user groups have been asked to rate top three hits per approach for sixty search items from the point of view of the needs of their professional target groups, namely second/foreign language (L2) teachers and lexicographers. This evaluation has shown, on the one hand, which of the two approaches to example rating (called in the text below algorithms #1 and #2) performs better in terms of finding better examples for each target user group; and on the other hand, which features evaluators associate with good examples. It has also facilitated statistic analysis of the “good” versus “bad” examples with reference to the measurable features, such as sentence length, word length, lexical frequency profiles, PoS constitution, dependency structure, etc. with a potential to find out new reliable classifiers.

Page Manager: Webmaster|Last update: 9/11/2012

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