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In this paper, an algorithm for extracting keywords without corpus is described. We use the co-occurrence information of the words and the biases of distribution to extract the more important words based on the most frequently appearing words so called reference words. Firstly, the most frequently terms are chosen
provide simple message analysis features such as browsing and simple keyword-based searching of the recorded messages. In this paper, we propose a system, called IMAnalysis, that supports intelligent chat message analysis using text mining techniques. The IMAnalysis system provides functions on chat message retrieval, social
, path length, landing position and fixation direction are extracted for classification purposes. Five categories of reading pattern have been defined and investigated in this study, namely, speed reading, slow reading, in-depth reading, skim-and-skip, and keyword spotting. We have recruited thirty subjects to participate
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