Surapant Meknavin

Learn More
This paper presents a method, called Adaptive Directed Acyclic Graph (ADAG), to extend Support Vector Machines (SVMs) for multiclass classification. The ADAG is based on the previous approach, the Decision Directed Acyclic Graph (DDAG), and is designed to remedy some weakness of the DDAG caused by its structure. We prove that the expected accuracy of the(More)
This paper presents an algorithm for selecting an appropriate classifier word for a noun. In Thai language, it frequently happens that there is fluctuation in the choice of classifier for a given concrete noun, both from the point of view of the whole speech community and individual speakers. Basically, there is no exact rule for classifier selection. As(More)
This paper presents a survey on computer and the internet usage in both governmental and private universities. Questionnaires were sent to the university administrators in the levels of department head, office head, associate dean and dean of 24 governmental universities and of 15 private universities. 46.7% of these questionnaires have been returned. The(More)
This paper presents an application of two machine learning algorithms, i.e., Winnow and RIPPER, and their comparison on the task of Thai named-entity identification. While most of previous works on this task are based on handcoded rules, we use learning algorithms to help automate the development of named-entity system. Since Thai language has no explicit(More)
Variations of word order are among the most well-known phenomena of natural languages. From st well represented sample of world languages, Steele[13] shows that about 76% of languages exhibit significant word order variation. In addition to the wellknown Walpiri(Australian language), several languages such as Japanese, Thai, German, Hindi, and Finnish also(More)
  • 1