Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/137835
Title: A dynamic and scalable evolutionary data mining and kdd for distributed environment
Researcher: Vaghela,Dineshkumar
Guide(s): Priyanka Sharma, Kalpdrum Passi
Keywords: Distributed Environment
Dynamic
Scalable
Data Mining
Decsion Tree
Central Processing
Intermediate Message Passing
Communication Overhear
Training time
Training Model
University: Gujarat Technological University
Completed Date: 21/01/2017
Abstract: Due to vast use of internet in distributed environment has generated an urgent need for new techniques and tools that can intelligently automatically transform the processed data into useful information and knowledge The heterogeneous nature of data resultant models and techniques raise problems on how to generalize knowledge in order to have global view of the phenomena across the entire organization The centralized and intermediate message passing approaches are not much efficient due to Storage cost Communication cost Computational cost Private and sensitive data The proposed framework and the algorithm is much efficient and fulfil the objectives such as to minimize the training time and communication overhead and to preserve the prediction quality newline
Pagination: 
URI: http://hdl.handle.net/10603/137835
Appears in Departments:Computer/IT Engineering

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01_title.pdfAttached File57.88 kBAdobe PDFView/Open
02_certificate.pdf73.48 kBAdobe PDFView/Open
03_abstract.pdf94.31 kBAdobe PDFView/Open
04_declaration.pdf73.58 kBAdobe PDFView/Open
05_acknowledgement.pdf74.68 kBAdobe PDFView/Open
06_contents.pdf56 kBAdobe PDFView/Open
07_list_of_tables.pdf49.66 kBAdobe PDFView/Open
08_list_of_figures.pdf64.13 kBAdobe PDFView/Open
09_abbreviations.pdf53.71 kBAdobe PDFView/Open
10_chapter1.pdf87.42 kBAdobe PDFView/Open
11_chapter2.pdf410.97 kBAdobe PDFView/Open
12_chapter3.pdf106.15 kBAdobe PDFView/Open
13_chapter4.pdf363.36 kBAdobe PDFView/Open
14_chapter5.pdf455.6 kBAdobe PDFView/Open
15_chapter6.pdf350.02 kBAdobe PDFView/Open
16_chapter7.pdf880.5 kBAdobe PDFView/Open
17_chapter8.pdf337.33 kBAdobe PDFView/Open
18_conclusion.pdf7.87 kBAdobe PDFView/Open


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