Title: Feature-based Thai Word Segmentation
Speaker: Paisarn Charoenpornsawat

Abstract:
Word Segmentation is a problem in several Asian language that have no
explicit word boundary delimiter, e.g. Chinese, Japanese, Korean and Thai.
We propose to use feature based approaches for Thai word segmenation. A
feature can be anything that tests for specific information in the context
arround the word in question, such as context words and collocations. To
automatically extract such features from a training corpus, we employ two
learning algorithms, namely RIPPER and Winnow. Experimental results show
that both algorithms appear to outperform the existing Thai word
segmentation methods, especially for context-dependent strings.