Abstract In the social network, people with same interest construct a group, where people can share their interesting contents. With the popularity of the mobile devices, mobile users can connect to the internet for services such as downloading videos, music and pictures anywhere at any time, which may cause heavy traffic burden on the core network. The service content (eg. video, picture, music) downloaded... In the social network, people with same interest construct a group, where people can share their interesting contents. With the popularity of the mobile devices, mobile users can connect to the internet for services such as downloading videos, music and pictures anywhere at any time, which may cause heavy traffic burden on the core network. The service content (eg. video, picture, music) downloaded and shared in the same social network interest group may always be similar, which may lead to repeated traffic transmitted in a short time period; on the other hand, the size of the service content may be very large for a single user, which will take it along time and spend much money to finish a complete service request or sharing. It is necessary to study how to reduce the requests in internet from the mobile users to reduce the flow on the core network, as well as reducing the economic cost and the service time, which is the main motivation of our research. Based on the universal mobile social network architecture, this paper proposed CAMPSNA: a cloud assisted mobile peer to peer social network architecture. In which, the cloud center is introduced to help the mobile devices offloading complex tasks to the cloud. The end devices in the architecture construct a local mobile peer to peer network to share their existing content based on their social relationships to reduce the burden of the cloud center. Read More Read Less

Abstract In view of the deficiency of the present attribute weight methods based on the rough sets theory, the author proposes one new comprehensive attribute weight method through studying deeply attribute importance on the basis of rough sets theory. The proposed method considers objective weight and subjective weight. The objective weight includes three factors, named as the importance of the attribute itself, the increment... In view of the deficiency of the present attribute weight methods based on the rough sets theory, the author proposes one new comprehensive attribute weight method through studying deeply attribute importance on the basis of rough sets theory. The proposed method considers objective weight and subjective weight. The objective weight includes three factors, named as the importance of the attribute itself, the increment of mutual information, and its own information entropy. The subjective weight is obtained by the experts with prior knowledge in the field. Experiment results prove that the new method not only overcomes the deficiency of the existing weight methods, but also is more in line with the actual situation. Read More Read Less