详情

原文传递 Preprocessing Techniques to Support Event Detection Data Fusion on Social Media Data.

题名：	Preprocessing Techniques to Support Event Detection Data Fusion on Social Media Data.
作者：	Davis, B. T.
关键词：	Social media, Data fusion, Data processing, Digital data, Social networks, Anomaly detection, Algorithms, Feature extraction, Event detection, Preprocessing techniques, Textual analysis algorithms, Image analysis algorithms, Cnn (convolutional neural networks)
摘要：	This thesis focuses on collection and preprocessing of streaming social media feeds for metadata as well as the visual and textual information. Today, news media has been the main source of immediate news events, large and small. However, the information conveyed on these news sources is delayed due to the lack of proximity and general knowledge of the event. Such news have started relying on social media sources for initial knowledge of these events. Previous works focused on captured textual data from social media as a data source to detect events. This preprocessing framework postures to facilitate the data fusion of images and text for event detection. Results from the preprocessing techniques explained in this work show the textual and visual data collected are able to be-proceeded into a workable format for further processing. Moreover, the textual and visual data collected are transformed into bag-of-words vectors for future data fusion and event detection.
报告类型：	科技报告