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ABSTRACT
<p><b>Abstract</b>—This paper presents a novel Fourier analysis-based approach to combine, transmit, and visualize decision trees in a mobile environment. Fourier representation of a decision tree has several interesting properties that are particularly useful for mining data streams from small mobile computing devices connected through limited-bandwidth wireless networks. This paper presents algorithms to compute the Fourier spectrum of a decision tree and outlines a technique to construct a decision tree from its Fourier spectrum. It offers a framework to aggregate decision trees in their Fourier representations. It also describes the MobiMine, a mobile data stream mining system, that uses the developed techniques for mining stock-market data from handheld devices.</p>
INDEX TERMS
Mobile data mining, decision trees, Fourier spectrum.
CITATION

B. Park and H. Kargupta, "A Fourier Spectrum-Based Approach to Represent Decision Trees for Mining Data Streams in Mobile Environments," in IEEE Transactions on Knowledge & Data Engineering, vol. 16, no. , pp. 216-229, 2004.
doi:10.1109/TKDE.2004.1269599
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