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IJSTR >> Volume 8 - Issue 8, August 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Mobile Commerce Pattern Mining Behavior Prediction Based On Kernel SVM

[Full Text]



N.Karthikeyan, Dr S.Selva Brunda



-mobile commerce, behavior prediction, transformation, kernel SVM, SIM



We suggest an implementation for the mining and prediction of mobile user’s actions and purchase transactions together. The implementation gives the user with data about that all shops a specific product is accessible and that shop gives the best proposal. With the help of this application we can create the Live shopping by the user without having to go to each shop and query. Mobile Commerce, also called as M-Commerce or commerce, is the aptitude to conduct commerce with the help of a mobile device. Research is performed using Mining and Prediction of Mobile Users’ Commerce Behaviors like their movements and purchase transactions. In our projected research we have envisioned to suggest a mobile commerce behavior prediction primarily the input information are taken from a mobile transaction database it comprises a store item information and item store information we have transform this information with the help of transformation have extract a data’s on the basis of a similarity bases now we have a store data and item data also it encompasses a store similarity and item similarity data’s from that we have taken a similarity data’s and stock that data’s these data’s are provided in to the Similarity Inference Model SIM for calculating the similarities amongst stores and items that are two basic mobile commerce entities measured in this paper these are given n to the prediction engine also it have a user transaction, identification and movement from these engine, we have envisage the user behavior with the help of Kernel based SVM.



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