Privacy-Preserved and Best-Effort Provisions of Cyber-I Information to Personalized Services

User information is needed for personalized services. Currently there are mainly two approaches to collect a user´s information, explicit approach by acquiring information directly from the user and implicit approach by gathering the user´s activities and behaviors almost without the user´s awareness. This paper is to study a new approach, which gets a user´s information from a Cyber-I that has kept certain information about the user. A Cyber-I, short for Cyber Individual, is a digital counterpart of a user (i.e., Real-I), and it contains three categories of a user´s information, basic data like a profile about the user, raw data like Web browsing history done by the user, and model like the user´s preference by analyses of the user´s browsing historic data. The main challenge in getting personal information from a Cyber-I is how to provide requested information to a personal service and sufficiently persevere the user´s privacy requirement. Thus, this paper is focused on providing Cyber-I information to personalized services by best-efforts provisions, simultaneously provide privacy preservation for Cyber-I, and building a Cyber-I Information Provision System (CIPS) to test the proposed new approach.