Download Advances in Intelligent IT - Active Media Technology 2006, by Y. Li, M. Looi, N. Zhong PDF

By Y. Li, M. Looi, N. Zhong

Within the nice electronic period, we're witnessing many quick medical and technological advancements in human-centered, seamless computing environments, interfaces, units, and structures with purposes starting from enterprise and communique to leisure and studying. those advancements are jointly top characterised as lively Media expertise (AMT), a brand new quarter of clever info know-how and machine technology that emphasizes the proactive, seamless roles of interfaces and platforms in addition to new media in all features of electronic lifestyles. An AMT dependent desktop procedure bargains prone that allow the swift layout, implementation, deploying and aid of personalized ideas. This publication brings jointly papers from researchers from various parts, resembling internet intelligence, facts mining, clever brokers, clever info use, networking and clever interface.IOS Press is a global technological know-how, technical and scientific writer of fine quality books for teachers, scientists, and execs in all fields. a few of the components we post in: -Biomedicine -Oncology -Artificial intelligence -Databases and data structures -Maritime engineering -Nanotechnology -Geoengineering -All facets of physics -E-governance -E-commerce -The wisdom economic climate -Urban stories -Arms regulate -Understanding and responding to terrorism -Medical informatics -Computer Sciences

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Extra info for Advances in Intelligent IT - Active Media Technology 2006, Proceedings of the 4th International Conference on Active Media Technology, AMT 2006, June 7-9, 2006, Brisbane, Australia

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10. Feedback and reward peers based on their performances on the task. 11. Based on the feedback update the manage agent’s profile. From Figure 1, it can be seen that when a recommender peer is requested to make a recommendation for a user, it acts as a manager agent. In the role of a manager agent, the recommender first generates a strategy about how and what to recommend to the user based on the user’s profile and request, then chooses a set of recommender peers (in this context, they act as contractor agents) based on the strategy and the profiles of peer recommenders, and makes requests for recommendations to these selected recommender peers.

W sdv (T ) 7. if w < max_diversity_treshold then 8. SCA = a sorted CA based on T 9. return first k contractor agents from SCA 10. otherwise 11. CA' {ai  CA | trust ( ai )  T } 12. SCA’ = a sorted CA’ based on Pm 13. if SCA '  k then 14. -T. Weng et al. / A Fair Peer Selection Algorithm 15. 16. otherwise return first k contractor agents from SCA’ The algorithm contractor_selection shows that the selection of contractor agents is not only by the trustworthiness, we also take the balance of trustworthiness into consideration in order to achieve global optimum performance of the interaction.

T. Weng et al. / A Fair Peer Selection Algorithm is often called “cold-start problem”) [5]. e. e. apply recommendation systems on to inter-organizational level), and more importantly, great business value might be generated during the resource sharing process among the organizations. In this paper, we describe a preliminary design of a distributed recommender system model that enables recommender systems in different organizations to share their recommendations boundlessly, and the algorithm that we employed to solve the peer selection problem in the proposed distributed recommender system is also presented.

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