Personalized Text Retrieval for Learners of Chinese as a Foreign Language

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationCOLING 2018 : The 27th International Conference on Computational Linguistics
Subtitle of host publicationProceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages3448–3455
ISBN (Electronic)9781948087506
Publication statusPublished - Aug 2018

Conference

TitleThe 27th International Conference on Computational Linguistics (COLING 2018)
LocationSanta Fe Community Convention Center
PlaceUnited States
CityNew Mexico
Period20 - 26 August 2018

Abstract

This paper describes a personalized text retrieval algorithm that helps language learners select the most suitable reading material in terms of vocabulary complexity. The user first rates their knowledge of a small set of words, chosen by a graph-based active learning model. The system trains a complex word identification model on this set, and then applies the model to find texts that contain the desired proportion of new, challenging, and familiar vocabulary. In an evaluation on learners of Chinese as a foreign language, we show that this algorithm is effective in identifying simpler texts for low-proficiency learners, and more challenging ones for high-proficiency learners.

Citation Format(s)

Personalized Text Retrieval for Learners of Chinese as a Foreign Language. / Yeung, Chak Yan; Lee, John.
COLING 2018 : The 27th International Conference on Computational Linguistics: Proceedings of the Conference. Association for Computational Linguistics (ACL), 2018. p. 3448–3455.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review