Extending Independent Component Analysis for Event Detection on Online Social Media

被引:0
|
作者
Hoang Long Nguyen [1 ]
Jung, Jason J. [1 ]
机构
[1] Chung Ang Univ, Dept Comp Engn, 84 Heukseok Ro, Seoul, South Korea
来源
INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2018, PT I | 2018年 / 11314卷
基金
新加坡国家研究基金会;
关键词
Social event; Independent component analysis; Noise reduction; Signal separation; ICA; IMPLEMENTATION; FRAMEWORK; REMOVAL;
D O I
10.1007/978-3-030-03493-1_82
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:792 / 800
页数:9
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