Discovery of Potential Topics from Blog Articles by Machine Learning

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Provided by: Advances in Computer Science : an International Journal (ACSIJ)
Topic: Enterprise Software
Format: PDF
In this paper, the authors present a method for potential topic discovery from blogsphere. They define a potential topic as an unpopular phrase that has potential to become a hot topic. To discover potential topics, this method builds a classifier to detect potentiality of a topic from topic frequency transitions in blog articles. First, this method extracts candidates of potential topics from categorized blog articles because categorization enables them to extract specialists. To extract potential topics from the candidates, a classifier for detecting potential topics is built from topic frequency transition data.
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