An Approach To Context-aware Service Pushing By Mobile And Cloud

With the development of information age and big data,people have gradually entered into the information overload era.The influx of large amounts information makes it difficult for user to filter.Service pushing system is playing an important role to solve this problem.Service pushing system provide valuable service information to the user who needs the information and help the service provider to find the appropriate user.However,the traditional way of recommendation has great limitations on the binary relationship between item and user.The system push information based on the analysis of item and user.But the information is static,it can not to reflect the user's current needs and preferences.The recommendation often makes the user unsatisfied.On the basis of push system,the context-aware push focuses on the analysis of the user's current geographic location,time and preference as implicit data.The push service information will also be changed according to the user's current environment.Through the improvement of the original push algorithm,user's context can effectively affect the recommendation result.We propose a hybrid approach for context-aware computing.The service information pushing based on the current context.Through the improvement of pushing algorithm,the approach not only filter the useful information effectively,but also delete the redundant or outdated service information automatically.The pushing results are simple and effective.The pushing performance is better than before.The context acquisition will be more real-time and accurate by mobile computing.The mobility and intelligent of mobile provides a more effective and real-time information sources.The introduction of cloud computing can effectively share the data calculation pressure.Cross platform collaboration barriers can also be resolved.User profiles will be structured in the cloud and shared with servers distributed around.The profile will be more safe.The security of user profile is also protected by the cloud platform.In this paper,we first discuss the problem of how to effectively solve the problem of data selection and data pushing in the era of data overload.We enumerate some common push algorithm and give the shortcomings and advantage of these algorithm.And the defects of traditional pushing system will also be shown.After that,we will show how context-aware computing can make up for the defects of recommender systems and give the advantage of context-aware computing in the field of recommendation.Finally,we will improve the performance of context-aware computing by explaining the characteristics of mobile computing and cloud computing.So as to show the effectiveness and value of the method proposed in this paper.The approach includes improvements in functionality and effectiveness such as metadata,update policies and EUD technologies.And the end of the paper,we will give the simulation experiment data as the proof of the effectiveness and performance improvement.