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With the popularity of virtual communities among network users,virtual community groups have become a small society,which can extract user-related privacy resources through the "virtual traces" left by users' browsing and user-generated content user published.Privacy resources can be classified into data resources,information resources and knowledge resources according to their characteristics,which constitute the data,information,knowledge,and wisdom graph (DIKW graph).There are four circulation processes for privacy resources in virtual communities,namely,the sensing,storage,transfern,and processing of privacy resources.The four processes are respectively completed by the three participants,the user,the AI system,and the visitor individually or in cooperation.The right to privacy includes the right to know,the right to participate,the right to forget,and the right to supervise.By clarifying the scope of privacy rights of the three participants in the four circulation processes,and combining the protection of privacy values,an anonymous protection mechanism,risk assessment mechanism and supervision mechanism are designed to build an AI governance legal framework for privacy protection of virtual communities.

With the development of the Web service technology, the service mode based software is widely used in the fields of health care, education and public transportation. However, Quality-of-Service(QoS)control is still one of the difficulties in the service technology. In the process of service combination, considering the design-time service and run-time service modes, two service design modes Over Design(OD)and Under Design(UD)are proposed. The variability space that constrains service combination is constructed to achieve the goal of QoS control. We show OD and UD cases in E-commence scenarios and use value based analysis to justify the significance of reducing OD and UD. [ABSTRACT FROM AUTHOR]

In this paper, we study QoS-aware cloud service composition based on time series, taking the sustaining change process of service QoS preference into research scope of cloud service composition, and transform the composition of cloud services into similarity comparison problems between time series. Euclidean distance and the extend Frobenius norm distance are used to measure similarity between two-dimensional time series respectively. In the next, the extend Frobenius norm distance or Euclidean distance based on principal component analysis and Brute-Force method are adopted to measure the similarity between multidimensional time series. Experiments show that the extend Frobenius norm distance has better performance on similarity measurement in time and accuracy. [ABSTRACT FROM AUTHOR]