HANS: A service-oriented framework for chinese language processing

Lung Hao Lee*, Kuei Ching Lee, Yuen Hsien Tseng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


A service-oriented architecture called as HANS is proposed to facilitate Chinese natural language processing. This unified framework seamlessly integrates fundamental NLP tasks including word segmentation, part-of-speech tagging, named entity recognition, chunking, paring, and semantic role labeling to enhance Chinese language processing functionality. A basic Chinese word segmentation task is used to illustrate the function of the proposed architecture. to demonstrate the effects. Evaluated benchmarks are taken from the SIGHAN 2005 bakeoff and the NLPCC 2016 shared task. We implement publicly released toolkits including Stanford CoreNLP, FudanNLP and CKIP as services in our HANS framework for performance comparison. Experimental results confirm the feasibility of the proposed architecture. Findings are also discussed to point to potential future developments.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 18th International Conference, CICLing 2017, Revised Selected Papers
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783319771120
Publication statusPublished - 2018
Event18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017 - Budapest, Hungary
Duration: 2017 Apr 172017 Apr 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10761 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2017


  • Chinese natural language processing
  • Chinese word segmentation
  • Service-oriented architecture

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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