Choochart Haruechaiyasak

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Traditional approaches for studying consumer behavior, such as marketing survey and focus group, require a large amount of time and resources. Moreover, some products, such as smartphones, have a short product life cycle. As an alternative solution, we propose a system, the Micro-blog Sentiment Analysis System (MSAS), based on sentiment analysis to(More)
In this paper, we analyze and compare various approaches for Thai word segmentation. The word segmentation approaches could be classified into two distinct types, dictionary based (DCB) and machine learning based (MLB). The DCB approach relies on a set of terms for parsing and segmenting input texts. Whereas the MLB approach relies on a model trained from a(More)
We propose a feature called category browsing to enhance the full-text search function of Thai-language news article search engine. The category browsing allows users to browse and filter search results based on some predefined categories. To implement the category browsing feature, we applied and compared among several text categorization algorithms(More)
—Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a(More)
Growth of microblogging “Twitter” is dramatic among online users in Thailand. Communication on Twitter is very lively and up-to-date since users Users often express their feelings and sentiments in Twitter posts related to current topics or new growing topic. While sentiment analysis on Twitter has challenges in language related issues, such(More)
In this paper, a method of automatically classifying Web documents into a set of categories using the fuzzy association concept is proposed. Using the same word or vocabulary to describe different entities creates ambiguity, especially in the Web environment where the user population is large. To solve this problem, fuzzy association is used to capture the(More)
Recent research in mining user access patterns for predicting Web page requests focuses only on consecutive sequential Web page accesses, i.e., pages which are accessed by following the hyperlinks. In this paper, we propose a new method for mining user access patterns that allows the prediction of multiple non-consecutive Web pages, i.e., any pages within(More)