Ohm Sornil, advisorSomnuk Sinthupoun2014-05-052014-05-052009http://repository.nida.ac.th/handle/662723737/283Thesis (Ph.D. (Computer Science))--National Institute of Development Administration, 2009Rhetorical Structure Analysis (RSA) explores Discourse Relations (DRs) among related Elementary Discourse Units (EDUs) in a Rhetorical Structure Tree (RS tree) to describe meaning in a text. It is very useful in many text processing tasks employing relationships among EDUs to use an input such as text understanding, summarization, discourse parsing, machine translation and question answering. The Thai language, with its distinctive linguistic characteristics, requires a unique technique. Thai linguistic characteristics have no explicit EDU boundaries, referred to as EDU constituent omissions. Within a Thai RS tree, Thai has adjacent markers, implicit markers and marker ambiguities in DR determination. This dissertation proposes a new approach to Thai RSA which consists of three steps. The first is EDU segmentation where EDUs are segmented by phrase and syntactic hidden Markov models which are derived from phrase and syntactic structure rules, respectively. The second is RS tree Construction, where an RS tree is constructed using a clustering technique with its similarity matrix calculated from the three Thai semantic rules: Repetition rules established from the repetition of EDU constituents, Omission rules established from the omission of EDU constituents, and Addition rules established by adding Markers into EDUs. In the final step, DR determination, decision tree learning whose features are derived by relating two EDUs in an RS tree using the semantic rules to determine Discourse Relations.99 leaves : ill. ; 30 cm.application/pdfengThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.P 98.3 So55 2009Computational linguisticsNatural language processing (Computer science)Thai language -- Rhetoric -- Computer programsThai rhetorical structure analysistext--thesis--doctoral thesis10.14457/NIDA.the.2009.139