A Kalman Filter Based Human-Computer Interactive Word Segmentation System for Ancient Chinese Texts

  • Tongfei Chen
  • Weimeng Zhu
  • Xueqiang Lv
  • Junfeng Hu
Conference paper

DOI: 10.1007/978-3-642-41491-6_3

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8202)
Cite this paper as:
Chen T., Zhu W., Lv X., Hu J. (2013) A Kalman Filter Based Human-Computer Interactive Word Segmentation System for Ancient Chinese Texts. In: Sun M., Zhang M., Lin D., Wang H. (eds) Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data. Lecture Notes in Computer Science, vol 8202. Springer, Berlin, Heidelberg

Abstract

Previous research showed that Kalman filter based humancomputer interaction Chinese word segmentation algorithm achieves an encouraging effect in reducing user interventions. This paper designs an improved statistical model for ancient Chinese texts, and integrates it with the Kalman filter based framework. An online interactive system is presented to segment ancient Chinese corpora. Experiments showed that this approach has advantage in processing domain-specific text without the support of dictionaries or annotated corpora. Our improved statistical model outperformed the baseline model by 30% in segmentation precision.

Keywords

Word Segmentation Human-Computer Interactive System Kalman Filter Ancient Chinese Corpus Processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tongfei Chen
    • 1
  • Weimeng Zhu
    • 1
  • Xueqiang Lv
    • 3
  • Junfeng Hu
    • 2
  1. 1.School of Electronics Engineering & Computer SciencePeking UniversityBeijingP.R. China
  2. 2.Key Laboratory of Computational Linguistics, Ministry of EducationPeking UniversityBeijingP.R. China
  3. 3.Beijing Key Laboratory of Internet Culture and Digital Dissemination ResearchBeijing Information Science and Technology UniversityBeijingP.R. China

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