Full-text Search for Thai Information Retrieval Systems

While there have been a lot of efficient full-text search algorithms developed for English documents, these algorithms can be directly used for other languages, e.g. Chinese, Japanese, Thai and so on. However, due to idiosyncrasies of each individual language, directly applying such algorithms may not be suitable for the language considered. This paper proposes a simplification of Boyer-Moore algorithm, called BMT, in order to reduce computation and makes it appropriate for Thai full-text. To investigate the efficiency, the comparison of BMT with other search algorithms is evaluated. Moreover, we applied syllable-like segmentation, called Thai character clusters (TCCs), to improve searching efficiency in Thai documents by grouping Thai characters into inseparable units. The TCC is based on the spell features of Thai language. Comparing with traditional full-text searching methods, this approach can improve not only searching time and memory consumption but also searching accuracy. The experimental results evidence that searching methods using TCC outperform the traditional methods in full-text search algorithm.