V. K. Mahesh Joshi Eui-Hong, George Karypis. Parallel algorithms in data mining. Home/Search Document Details and Download
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Efficient Parallel Frequency Mining Based On A Novel Top-Down.. - Özkural (2002) (Correct)
....High performance computing has become an essential element of data mining as very large data is becoming available in both scienti c and business applications. As the sensor data and simulation results accumulate, scientists need better means to analyze them for discovering new knowledge [53, 25]. We must depend on parallel systems to analyze the massive volumes of data in frequency mining problem [5, 78] Zaki points out to the challenges for obtaining good performance: communication minimization, load balancing, suitable data Algorithm 4 FP Growth(T ree; 2: for all combination ....
V. K. Mahesh Joshi Eui-Hong, George Karypis. Parallel algorithms in data mining.
A Middleware for Developing Parallel Data Mining Applications - Jin, Agrawal (2001) (1 citation) (Correct)
....have also been observed by Skillicorn [37, 36] Our work is different in offering a middleware to exploit the similarity, and ease parallel application development. The challenges in scalable and parallel data mining we listed in Section 1 have also been observed by a number of other authors [5, 13, 21, 26, 28, 31, 36]. Several runtime support libraries and file systems have been developed to support efficient I O in a parallel environment [15, 34] most noticeable among these is the PASSION library designed by Alok Choudhary s group [39, 40] They usually provide a collective I O interface, in which all ....
Mahesh V. Joshi, Eui-Hong (Sam) Han, George Karypis, and Vipin Kumar. Parallel algorithms for data mining. In J. Dongarra, I. Foster, G. Fox, K. Kennedy, and A. White, editors, CRPC Parallel Computing Handbook. Morgan Kaufmann, 2000.
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