Mining And Prediction Research For Mobile Access Pattern Based On Context Awareness

The rapid advance of ubiquitous mobile network technologies enables the provision of rich kinds of mobile services based on context awareness for mobile users. The future wireless network, as air and water, penetrate our daily life and work, which will not be passive to satisfy mobile end user's requirements, but initiate actively to aware end users context's shift and analyze their personal requirement, and then exchange their information. The past studies on mobile services focused mainly on the provision of anytime and anywhere services. However, this is insufficient for the future mobile internet systems. The context characteristics, such as the user's location, the user's preference, the user's service request time and the user's historical behavior, should also be considered in order to provide the users with context-aware services that will benefit the users.The development of future mobile internet has allowed the mobile users to request various kinds of services by mobile devices at anytime and anywhere. Helping the users obtain needed information effectively is an important issue in the future mobile internet systems. Discovery and analysis of mobile user's diverse behavior can highly benefit the enhancements on mobile internet system performance and quality of services. Obviously, the mobile user's behavior patterns, in which the location and the service are inherently coexistent, become more complex than those of the traditional web systems. Therefore, this paper makes a deep research and analysis on sequence mobile access pattern mining method, privacy limiting method in context awareness data mining and prediction algorithm for mobile access pattern, and presents the reasonable theoretical solutions on the key technical issues:(1) Sequence mobile access pattern mining research for mobile user;The mobile user's diverse behavior patterns are usually associated with the user's location, the user's service request and the user's service time. Recently, some studies have been done on mining sequence mobile access pattern with the user's location and service request considered. Some research teams also simply consider the user's service time characteristic, they divide one day, 24 hours, into several section, Thus, the mobile access pattern for every time section was analyzed, so that some key sequence mobile access patterns are easy to be divided by the time segment. But, no studies have focused on continuous time sequence mobile access pattern so far, and the relative research is in the beginning phase, and there are more relative work need to do. (2) Personal privacy leakage research based on context awareness service;With the development of mobile network technologies and mobile commerce, personal privacy leakage had not been a new issue. Especially, privacy leakage and protection issues had affected the future development of new mobile commerce. Context awareness services enable user's convenient life, whereas, privacy leakage issues from context awareness service will be worried about by mobile users simultaneously. Therefore, how to limit mobile user's privacy leakage will be the future context awareness service's key research content.(3) Prediction research on sequence mobile access pattern;Recently, few studies have been done on mobile access pattern prediction based on context awareness, and the relative research teams mainly focused on web data mining and prediction. However, both of them have some similarities, that is, all of them predict mobile users' future behavior based on their historical behavior information. However, there are also some dissimilarities between mobile access pattern prediction and web data prediction. Web data prediction mainly considers below factors, such as user session, URL linkage etc., while mobile access pattern prediction mainly involves below factors, such as mobile user's location, mobile service time and mobile user's service request etc.. Therefore, they need to design different prediction solutions to predict future mobile user behavior pattern based on their similarities and dissimilarities. How to design sequence mobile access pattern prediction algorithm is considered as the paper's key research content.In conclusion, sequence mobile access pattern prediction research based on context awareness is just in a beginning stage for the international research teams, and thus how to design mobile access pattern's multi-dimension model including the user's location, the user's service request and service time considered will be an important research area.