Abstract
To predict the tendency of Micro-blog information dissemination, provide the early warning of the Internet emergencies, and contribute to the content security of micro-blog, the paper offers a platform for Micro-blog information perceiving and mining. This platform is an integration of Micro-blog data collection and processing module, topic detection and tracking module, user behavior analysis module, trend prediction module, etc. It could access and analyze micro-blog information automatically, leading a positive significance to grasp the emergencies on micro-blog. This paper puts forward methods based on the Latent Dirichlet Allocation (LDA) document clustering and hot topics prediction, which could analysis and predict the micro-blog data effectively, avoiding the problems in the traditional algorithm. Also, these methods have a higher accuracy for clustering and prediction.
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Acknowledgments
This work has been supported by the National Natural Science Foundation of China under Grant 61172072, 61271308, the Beijing Natural Science Foundation under Grant 4112045, the Research Fund for the Doctoral Program of Higher Education of China under Grant W11C100030, the Beijing Science and Technology Program under Grant Z121100000312024.
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Wang, X., Xiong, F., Liu, Y. (2014). Research on Micro-Blog Information Perception and Mining Platform. In: Huang, YM., Chao, HC., Deng, DJ., Park, J. (eds) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Lecture Notes in Electrical Engineering, vol 260. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7262-5_85
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DOI: https://doi.org/10.1007/978-94-007-7262-5_85
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