Utilizing theweb for automatic word spacing

Gumwon Hong, Jeong Hoon Lee, Young In Song, Do Gil Lee, Hae Chang Rim

Research output: Contribution to journalArticlepeer-review


This paper presents a new approach to word spacing problems by mining reliable words from the Web and use them as additional resources. Conventional approaches to automatic word spacing use noisefree data to train parameters for word spacing models. However, the insufficiency and irrelevancy of training examples is always the main bottleneck associated with automatic word spacing. To mitigate the data-sparseness problem, this paper proposes an algorithm to discover reliable words on the Web to expand the vocabularies and a model to utilize the words as additional resources. The proposed approach is very simple and practical to adapt to new domains. Experimental results show that the proposed approach achieves better performance compared to the conventional word spacing approaches.

Original languageEnglish
Pages (from-to)2553-2556
Number of pages4
JournalIEICE Transactions on Information and Systems
Issue number12
Publication statusPublished - 2009


  • Word segmentation
  • Word spacing

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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