Automatic extraction of new words based on Google News corpora for supporting lexicon-based Chinese word segmentation systems

Chin Ming Hong, Chih Ming Chen*, Chao Yang Chiu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


Chinese word segmentation is an essential step in a processing of Chinese natural language because it is beneficial to the Chinese text mining and information retrieval. Currently, the lexicon-based Chinese word segmentation scheme is widely adopted, which can correctly identify Chinese sentences as distinct words from Chinese language texts in real-word applications. However, the word identification ability of the lexicon-based scheme is highly dependent with a well prepared lexicon with sufficient amount of lexical entries which covers all of the Chinese words. In particular, this scheme cannot perform Chinese word segmentation process well for highly changeable texts with time, such as newspaper articles and web documents. This is because highly changeable documents often contain many new words that cannot be identified by a lexicon-based Chinese word segmentation system with a constant lexicon. Moreover, to maintain a lexicon by manpower is an inefficient and time-consuming job. Therefore, this study proposes a novel statistics-based scheme for extraction of new words based on the categorized corpora of Google News retrieved automatically from the Google News site to promote the word identification ability for lexicon-based Chinese word segmentation systems. Since corpora of news almost contain all words used in daily life, to extract news words from corpora of news and to incrementally add them into lexicon for lexicon-based Chinese word segmentation systems provide benefits in terms of automatically constructing a professional lexicon and enhancing word identification capability. Compared to another proposed scheme of new word extraction, the experimental results indicated that the proposed extraction scheme of new words not only more correctly retrieves new words from the categorized corpora of Google News, but also obtains larger amount of new words. Moreover, the proposed scheme of new word extraction has been applied to automatically expand the lexicon of the Chinese word segmentation system ECScanner (A Chinese Lexicon Scanner with Lexicon Extension). Currently, the ECScanner has been published on the Web to provide Chinese word segmentation service based on Web service. Experimental results also confirmed that ECScanner is superior to CKIP (Chinese knowledge information processing) in identifying meaningful Chinese words.

Original languageEnglish
Pages (from-to)3641-3651
Number of pages11
JournalExpert Systems with Applications
Issue number2 PART 2
Publication statusPublished - 2009 Mar


  • Chinese word segmentation
  • Information retrieval
  • Natural language processing
  • New word extraction

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence


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