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Prediction for Type of Mobile Application Based on User’s Behavior
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| Author:
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S. SRIVIDHYA, SORNALAKSHMI, S. SINDHU, S. NITHIYA
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| Abstract:
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Advances in smart phone innovation have empowered the predominance of versatile applications. Such an assortment of portable applications makes the smart phone all the more fascinating and more humanized, and running these applications has become the major capacity of smart phones. In this smart application trending environment, both application developers and researchers are paying more concentration towards identifying suitable application for the customers based on their characteristics and need. A challenging task now is how to predict the category of application suitable for the mobile users by utilizing different user characteristic parameters such as age group, gender, behavior, etc. In this paper we proposed a prediction model for choosing the type of application by using machine learning algorithms SVM and ANN. Both of the prediction algorithms can be used for predicting the mobile application type for users in real-time mobile environment. The experiments on the collected real-world data validate the ability of our prediction methods.
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| Keyword:
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Mobile Application, SVM, ANN.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.01.229
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| Download:
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