A New Model for Automatic Sentence Segmentation


  •  Funkun Xing    

Abstract

Context Overlapping Model (COM) is presented in this article for the task of Automatic Sentence Segmentation (ASS). Comparing with HMM, COM expands observation from single word to n-gram unit and there is an overlapping part between the neighboring units. Due to the co-occurrence constraint and transition constraint, COM model reduces the search space and improves tagging accuracy. We treated ASS as a task of sequence labeling and applied 2-gram COM to it. The experiment results show that the overall correct rate of the open test is as high as 90.11%, which is significantly higher than the baseline model (second order HMM), which is 85.16%.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: quarterly

Journal Metrics

WJCI (2020): 0.439

Impact Factor 2020 (by WJCI): 0.247

Google Scholar Citations (March 2022): 6907

Google-based Impact Factor (2021): 0.68

h-index (December 2021): 37

i10-index (December 2021): 172

(Click Here to Learn More)

Contact