Finding Short Patterns to Classify Text Documents
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Author(s)
An, Jiyuan
Chen, Yi-Ping Phoebe
Griffith University Author(s)
Year published
2006
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Many classification methods have been proposed to find patterns in text documents. However, according to Occam's razor principle, "the explanation of any phenomenon should make as few assumptions as possible", short patterns usually have more explainable and meaningful for classifying text documents. In this paper, we propose a depth-first pattern generation algorithm, which can find out short patterns from text document more effectively, comparing with breadth-first algorithmMany classification methods have been proposed to find patterns in text documents. However, according to Occam's razor principle, "the explanation of any phenomenon should make as few assumptions as possible", short patterns usually have more explainable and meaningful for classifying text documents. In this paper, we propose a depth-first pattern generation algorithm, which can find out short patterns from text document more effectively, comparing with breadth-first algorithm
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Conference Title
2006 IEEE / WIC / ACM International Conference on Web Intelligence (WI-2006)
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