Mobile User Behavior and Pattern Mining Using Data Mining

Download Project Document/Synopsis

There are wide range of potential mobile applications due to which mobile commerce had received a lot of interests from both of the industry and academia. Most of the users make transaction through mobile phones. In order to monitor the whole transaction process made through mobile phones, we propose a system where user’s mobile commerce behaviours are predicted. In this project we use data mining algorithm to predict the user’s mobile commerce behaviours such as their movements and purchase transactions. Here we explore a new data mining capability for a mobile commerce environment based on location based service. Our proposed system will predict mobile user’s movements and purchase transactions. This system is a web application where user will purchase resources that are available on the website. We used unique algorithm where the system will measure the similarities among stores and items. This system use certain pattern mining to find the mobile user’s movement and will predict the future mobile user behaviours. Location-based service is used to search the stores and items previously unknown to a user. The role of the admin is to monitor the whole transaction process, so there will be a secure transaction. This system will motivate many product based firms to sell their products online due to which they can easily get to know the demand of the user and can target right customer based on the products.



Advantages
  • This system will allow many users to make transaction securely as whole transaction being monitored by the system.
  • This system will motivate many product based firms to sell their products online.
  • This system will help supplier to know demand of the user.
  • This system will help the salesperson to target the right consumers.
Disadvantages
  • If internet connection fails, this system won’t work.
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