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Hillol Kargupta, ByungHoon Park, "A Fourier SpectrumBased Approach to Represent Decision Trees for Mining Data Streams in Mobile Environments," IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 2, pp. 216229, February, 2004.  
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@article{ 10.1109/TKDE.2004.1269599, author = {Hillol Kargupta and ByungHoon Park}, title = {A Fourier SpectrumBased Approach to Represent Decision Trees for Mining Data Streams in Mobile Environments}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {16}, number = {2}, issn = {10414347}, year = {2004}, pages = {216229}, doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2004.1269599}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  A Fourier SpectrumBased Approach to Represent Decision Trees for Mining Data Streams in Mobile Environments IS  2 SN  10414347 SP216 EP229 EPD  216229 A1  Hillol Kargupta, A1  ByungHoon Park, PY  2004 KW  Mobile data mining KW  decision trees KW  Fourier spectrum. VL  16 JA  IEEE Transactions on Knowledge and Data Engineering ER   
Abstract—This paper presents a novel Fourier analysisbased 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 limitedbandwidth 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 stockmarket data from handheld devices.
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