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Word segmentation based on database semantics in NChiql

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Abstract

In this paper a novel word-segmentation algorithm is presented to delimit words in Chinese natural language queries in NChiql system, a Chinese natural language query interface to databases. Although there are sizable literatures on Chinese segmentation, they cannot satisfy particular requirements in this system. The novel word-segmentation algorithm is based on the database semantics, namely Semantic Conceptual Model (SCM) for specific domain knowledge. Based on SCM, the segmenter labels the database semantics to words directly, which eases the disambiguation and translation (from natural language to database query) in NChiql.

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Authors and Affiliations

  1. School of Information, Renmin University of China, 100872, Beijing, P.R. China

    Meng Xiaofeng, Liu Shuang & Wang Shan

Authors
  1. Meng Xiaofeng
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  2. Liu Shuang
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  3. Wang Shan
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Corresponding author

Correspondence to Meng Xiaofeng.

Additional information

This work is supported by the National Natural Science Foundation of China under grant No.69633020.

MENG Xiaofeng is an associate professor of School of Information, Renmin University of China. He obtained the M.S. degree from Renmin University of China in 1993 and Ph.D. degree from the Institute of Computing Technology, the Chinese Academy of Sciences in 1999. His research interests include database systems, natural language interface, mobile and embedded software, and Web application.

LIU Shuang is a Ph.D. candidate at Institute of Computing Technology, the Chinese Academy of Sciences. She obtained the M.S. degree from Renmin University of China in 1999. Her research interests include database systems.

WANG Shan is a professor and dean of School of Information, Renmin University of China. She obtained the M.S. degree from Renmin University of China in 1982. Her research interests include database systems, datawarehouse & data mining, and information systems.

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Meng, X., Liu, S. & Wang, S. Word segmentation based on database semantics in NChiql. J. Comput. Sci. & Technol. 15, 346–354 (2000). https://doi.org/10.1007/BF02948870

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  • DOI: https://doi.org/10.1007/BF02948870

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