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With the rapid spread of Internet and the mobile web, the number of news pages is increasing quickly as well as the content of news becomes highly dynamic. It's difficult for normal users to obtain specific information contained in a mass of news streams. So it's of great research significance to study how to analyze massive news, detect and track news hotspots automatically. This research proposes...
The lasting popularity of many social Q&A websites, such as Yahoo! Answers and ResearchGate, has become valuable knowledge repositories for people to search for answers to questions in various aspects in life. Finding the most relevant questions is often a non-trivial task, and a fine-grained classification system of questions will be an important aid. Existing work mainly focused on classifying...
Document clustering as an unsupervised approach extensively used to navigate, filter, summarize and manage large collection of document repositories like the World Wide Web (WWW). Recently, focuses in this domain shifted from traditional vector based document similarity for clustering to suffix tree based document similarity, as it offers more semantic representation of the text present in the document...
With a rapid growth of the internet communication, many types of text are produced. They can convey the meanings that can contribute to text categorization. Emotion classification also becomes more interesting, but emotion classification in Thai text is still not able to be correctly classified. Thus, this paper proposes a novel approach that takes advantage of bi-words occurrence to classify emotion...
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