TY - JFULL AU - Sunee Pongpinigpinyo and Wanchai Rivepiboon PY - 2008/7/ TI - Distributional Semantics Approach to Thai Word Sense Disambiguation T2 - International Journal of Computer and Information Engineering SP - 2240 EP - 2245 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/12429 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 18, 2008 N2 - Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely  /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation. ER -