Learning Chinese polarity lexicons by integration of graph models and morphological features

Bin LU, Yan SONG, Xing ZHANG, Ka Yin Benjamin TSOU

Research output: Chapter in Book/Report/Conference proceedingChapters

8 Citations (Scopus)

Abstract

This paper presents a novel way to learn Chinese polarity lexicons by using both external relations and internal formation of Chinese words, i.e. by integrating two kinds of different but complementary models: graph models and morphological feature-based models. The polarity detection is first treated as a semi-supervised learning in a graph, and then machine learning is used based on morphological features of Chinese words. The results show that the integration of morphological feature-based models and graph models significantly outperforms the baselines. Copyright © 2010 Springer-Verlag Berlin Heidelberg.
Original languageEnglish
Title of host publicationInformation Retrieval Technology: 6th Asia Information Retrieval Societies Conference, AIRS 2010, Taipei, Taiwan, December 1-3, 2010. Proceedings
EditorsPu-Jen CHENG , Min-Yen KAN , Wai LAM , Preslav NAKOV
Place of PublicationBerlin, Germany
PublisherSpringer-Verlag
Pages466-477
ISBN (Print)9783642171871, 3642171877, 9783642171864, 3642171869
DOIs
Publication statusPublished - 2010

Citation

Lu, B., Song, Y., Zhang, X., & Tsou, B. K. (2010). Learning Chinese polarity lexicons by integration of graph models and morphological features. In P.-J. Cheng, M.-Y. Kan, W. Lam & P. Nakov (Eds.), Information Retrieval Technology: 6th Asia Information Retrieval Societies Conference, AIRS 2010, Taipei, Taiwan, December 1-3, 2010. Proceedings (pp. 466-477). Berlin, Germany: Springer-Verlag.

Keywords

  • Polarity lexicon induction
  • Graph models
  • Chinese morphology

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