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With the fast growth of computational biometric and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is a critical problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including the curse of dimensionality and more crucial the meaningfulness of the similarity measure in the high dimension space etc. This paper provides a review of various challenges, techniques for analysis, and dimensionality reduction of high dimensional data.
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