WeiboFinder : A topic-based Chinese word finding and learning system

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

1 Scopus Citations
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Author(s)

  • Yi Cai
  • Kinkeung Lai
  • Li Yao
  • Jun Zhang
  • Jingjing Li
  • Xingdong Jia

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationAdvances in Web-Based Learning – ICWL 2017
Subtitle of host publication16th International Conference, Cape Town, South Africa, September 20-22, 2017, Proceedings
EditorsHaoran Xie, Elvira Popescu, Gerhard Hancke, Baltasar Fernández Manjón
PublisherSpringer, Cham
Pages33-42
ISBN (Electronic)978-3-319-66733-1
ISBN (Print)978-3-319-66732-4
Publication statusPublished - Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10473 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title16th International Conference on Web-based learning (ICWL 2017)
PlaceSouth Africa
CityCape Town
Period20 - 22 September 2017

Abstract

With the explosive growth of user-generated data in social media websites such as Twitter and Weibo, a lot of research has been conducted on using user-generated data for web-based learning. Finding users’ desired data in an effective way is critical for language learners. Social media websites provide diversified data for language learners and some new words such as cyberspeak could only be learned in these online communities. In this paper, we present a system called WeiboFinder to suggest topic-based words and documents related to a target word for Chinese learners. All the words and documents are from the Chinese social media website: Weibo. Weibo is one of the largest microblog social meida websites in China which has similar functions as Twitter. The experimental results show that the proposed method is effective and better than other methods. The topics from our method are more interpretable and topic-based words are useful for Chinese learners.

Research Area(s)

  • Chinese learning, Semantic computing, Social media, Text mining, Topic modeling

Citation Format(s)

WeiboFinder : A topic-based Chinese word finding and learning system. / Chen, Wenhao; Cai, Yi; Lai, Kinkeung; Yao, Li; Zhang, Jun; Li, Jingjing; Jia, Xingdong.

Advances in Web-Based Learning – ICWL 2017: 16th International Conference, Cape Town, South Africa, September 20-22, 2017, Proceedings. ed. / Haoran Xie; Elvira Popescu; Gerhard Hancke; Baltasar Fernández Manjón. Springer, Cham, 2017. p. 33-42 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10473 LNCS).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)