Investigating Chinese HE EFL Classrooms - Using Collaborative Learning to Enhance Learning (Paperback, Softcover reprint of the original 1st ed. 2015)


This book presents a study on corpus-driven distribution as the main method of prediction, concentrating on individual semantic features to predict the senses of non-defined words by using corpora and tools, such as the Chinese Gigaword Corpus, HowNet, Chinese Wordnet, and XianDai HanYu CiDian (Xian Han). With the help of these corpora, the study determines the collocation clusters of four target words: chi1 "eat," wan2 "play," huan4 "change" and shao1 "burn" through character and concept similarities. The results of this sense prediction study demonstrate that it was able to use off-line tasks to test some participants' intuition, which supports the theory that different clusters can represent different senses when pursuing a corpus-based, computational approach.

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Product Description

This book presents a study on corpus-driven distribution as the main method of prediction, concentrating on individual semantic features to predict the senses of non-defined words by using corpora and tools, such as the Chinese Gigaword Corpus, HowNet, Chinese Wordnet, and XianDai HanYu CiDian (Xian Han). With the help of these corpora, the study determines the collocation clusters of four target words: chi1 "eat," wan2 "play," huan4 "change" and shao1 "burn" through character and concept similarities. The results of this sense prediction study demonstrate that it was able to use off-line tasks to test some participants' intuition, which supports the theory that different clusters can represent different senses when pursuing a corpus-based, computational approach.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Release date

August 2016

Availability

Expected to ship within 10 - 15 working days

First published

2015

Authors

Dimensions

235 x 155 x 18mm (L x W x T)

Format

Paperback

Pages

310

Edition

Softcover reprint of the original 1st ed. 2015

ISBN-13

978-3-662-52532-6

Barcode

9783662525326

Categories

LSN

3-662-52532-1



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