Abstract
Social network has been a widely accepted way for people to communicate and interact online. However, few of existing works studied temporal dimension in assessing the authority of nodes on social networks. In this paper, a novel Temporal PageRank (T-PR) algorithm is proposed for analyzing the authority of nodes. Three temporal factors are adopted to personalize PageRank, which favors the nodes that are more important to people. They are Built-up Time-length Factor (BTF), Frequency Factor (FF), and Similarity Factor (SF). The experiments on a real data set demonstrate T-PR algorithm provides the best ranking results over recent competitor methods.
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Acknowledgments
This work was partially sponsored by Grant FDCT/106/2012/ A3, FDCT/116/2013/A3 from Fund of Science and Technology Development of Macau Government and MYRG105-FST13-GZG from University of Macau Research Committee.
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Hu, W., Zou, H., Gong, Z. (2015). Temporal PageRank on Social Networks. In: Wang, J., et al. Web Information Systems Engineering – WISE 2015. WISE 2015. Lecture Notes in Computer Science(), vol 9418. Springer, Cham. https://doi.org/10.1007/978-3-319-26190-4_18
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DOI: https://doi.org/10.1007/978-3-319-26190-4_18
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