Todsanai Chumwatana

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This paper proposes a non-segmented document clustering method using self-organizing map (SOM) and frequent max substring technique to improve the efficiency of information retrieval. SOM has been widely used for document clustering and is successful in many applications. However, when applying to non-segmented document, the challenge is to identify any(More)
Thai language is considered as a non-segmented language where words are a string of symbols without explicit word boundaries, and also the structure of written Thai language is highly ambiguous. This problem causes an indexing technique has become a main issue in Thai text retrieval. To construct an inverted index for Thai texts, an index terms extraction(More)
Since the number of electronics non-segmented language documents is growing very fast, efficient document clustering techniques for non-segmented languages are needed as a tool in today’s world where a lot of documents are stored and retrieved electronically. It enables one to group the similar documents using keywords or terms of the clusters. Thus(More)
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