Extending Independent Component Analysis for Event Detection on Online Social Media

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Abstract

In this paper, we propose a new approach for filtering noises from social event signals by using independent component analysis technique. With a case study about two practical events, we prove that our approach is feasible. Besides, this idea is also to acquire high adaptability and extensibility property because we use only temporal signals of social events as inputs without requiring any more information. Moreover, our approach can be used as pre-processing step for other signal-based event discovering algorithms.

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Nguyen, H. L., & Jung, J. J. (2018). Extending Independent Component Analysis for Event Detection on Online Social Media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11314 LNCS, pp. 792–800). Springer Verlag. https://doi.org/10.1007/978-3-030-03493-1_82

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