  Rhetorical structure analysis (RSA) explores discourse relations among
elementary discourse units (EDUs) in a text. It is very useful in many text
processing tasks employing relationships among EDUs such as text understanding,
summarization, and question-answering. Thai language with its distinctive
linguistic characteristics requires a unique technique. This article proposes
an approach for Thai rhetorical structure analysis. First, EDUs are segmented
by two hidden Markov models derived from syntactic rules. A rhetorical
structure tree is constructed from a clustering technique with its similarity
measure derived from Thai semantic rules. Then, a decision tree whose features
derived from the semantic rules is used to determine discourse relations.
