Abstract
The development of SNS provides a new platform and application prospect for the realization of Personalized Recommendation System. It is becoming a fire new research hot spot in social science and e-commence about how to apply community discovery algorithm (CDA) to find community structures in large network and to effectively conduct personalized recommendation. In terms of our recent research, we applied PSO based CDA as principle to divide social communities and based on this to conduct personalized recommendation in a scientific paper management system. The system’s running results proved that by applying PSO based CDA, the accuracy of PR and the popularity of the platform had been both improved greatly.
Supported by“the Fundamental Research Funds for the Central Universitie.
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References
Kobsa, J., Koenemann, J., Pohl, W.: Personalized hypermedia presentation techniques for improving online customer relationships. The Knowledge Engineering Review, 111–155 (2001)
Lee, H.-C., Lee, S.-J., Chung, Y.-J.: A Study on the Improved Collaborative Filtering Algorithm for Recommender System. In: Fifth International Conference on Software Engineering Research, Management and Applications, pp. 297–304 (2007)
Nakagawa, M., Mobasher, B.: A Hybrid Web Personalization Model Based on Site Connectivity. In: The Fifth International WEBKDD Workshop: Web mining as a Premise to Effective and Intelligent Web Applications, pp. 59–70 (2003)
Wu, Y.-H., Chen, Y.-C., Chen, A.L.P.: Enabling Personalized Recommendation on the Web based on User Interests and Behaviors. In: 11th International Workshop on research Issues in Data Engineering (2001)
Li, X.: Adaptively Choosing Neighbourhood Bests Using Species in a Particle Swarm Optimizer for Multimodal Function Optimization. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 105–116. Springer, Heidelberg (2004)
Ma, R., Wang, X.: Community detection algorithm based on clustering coefficient (unpublished)
Ma, R., Wang, X.: Research of Community Discovery Algorithm Guided by Multimodal Function Optimization. In: Qi, L. (ed.) ISIA 2010. CCIS, vol. 86, pp. 678–683. Springer, Heidelberg (2011)
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Ma, R., Deng, G., Wang, X., Ailinna (2012). The Application of the PSO Based Community Discovery Algorithm in Scientific Paper Management SNS Platform. In: Zhang, W. (eds) Software Engineering and Knowledge Engineering: Theory and Practice. Advances in Intelligent and Soft Computing, vol 162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29455-6_91
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DOI: https://doi.org/10.1007/978-3-642-29455-6_91
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