To improve the similarity measurement between users, a similarity measurement approach incorporating clusters of intrinsic user groups（ SMCUG） is proposed considering the social information of users. The approach co...
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To improve the similarity measurement between users, a similarity measurement approach incorporating clusters of intrinsic user groups（ SMCUG） is proposed considering the social information of users. The approach constructs the taxonomy trees for each categorical attribute of users. Based on the taxonomy trees, the distance between numerical and categorical attributes is computed in a unified framework via a proper weight. Then, using the proposed distance method, the nave k-means cluster method is modified to compute the intrinsic user groups. Finally, the user group information is incorporated to improve the performance of traditional similarity measurement. A series of experiments are performed on a real world dataset, M ovie Lens. Results demonstrate that the proposed approach considerably outperforms the traditional approaches in the prediction accuracy in collaborative filtering.
Network management has widely adopted multi-agent architecture, and AGIMA is one of the successful prototypes that have developed mobile code facilities and group management functions. Taking consideration on the requ...
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Network management has widely adopted multi-agent architecture, and AGIMA is one of the successful prototypes that have developed mobile code facilities and group management functions. Taking consideration on the requirements of exchange and sharing of network management information between agents, the network management information described by next generation structure of management information can be represented as knowledge by XML-based resource description framework. These efforts need integration of some newer toolkit software and become foundation for introduction of network management intelligence into agents.
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