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Titlebook: Computational Intelligence and Intelligent Systems; 6th International Sy Zhenhua Li,Xiang Li,Zhihua Cai Conference proceedings 2012 Springe

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https://doi.org/10.1007/978-3-658-29756-5cy. We proposed a new recommendation method by combining the existed ’friend of friend’ algorithm and content-based recommendation. Through this method we can get more meaningful and apt recommendation outcomes and calculate more quickly in the large amount of data.
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The State of the Nation’s Narrativesto students. Considering the amount of resources required to support that process and the current restrictions on educational budgets there is an obvious need for further research in this area. In this paper we pay special attention on how to select the most suitable learning objects from a database.
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A Novel Heuristic Filter Based on Ant Colony Optimization for Non-linear Systems State Estimationthe state space dynamically in a similar scheme to the optimization algorithm, known as Continuous Ant Colony System. The performance of the new filter is evaluated for a nonlinear benchmark and the results are compared with those of Extended Kalman Filter and Particle Filter, showing improvements in terms of estimation accuracy.
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New Proofs for Several Combinatorial Identitiesntities are recovered. In addition, new proofs for two extensions of .-Chu-Vandermonde identity due to Fang[6] and two formulae on Stirling numbers of the second kind due to Chu and Wei[4] are also offered by means of combinatorial techniques.
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Construction of Standard College Tuition Model and Optimizationl model with the minimum difference between personal and social satisfaction and the greatest overall satisfaction, by using particle swarm algorithm to optimize the model, has given a reasonable charge tuition standard and national finance investment standard recommendations.
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Personalized Friend Recommendation in Social Network Based on Clustering Methodcy. We proposed a new recommendation method by combining the existed ’friend of friend’ algorithm and content-based recommendation. Through this method we can get more meaningful and apt recommendation outcomes and calculate more quickly in the large amount of data.
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On Dependences among Objects and Attributesto students. Considering the amount of resources required to support that process and the current restrictions on educational budgets there is an obvious need for further research in this area. In this paper we pay special attention on how to select the most suitable learning objects from a database.
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