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This minitrack encompasses papers of a quantitative, theoretical or applied nature that focus on: Content Mining of Social Media -- discovery of patterns from the text, images, audio, video and other data generated by Social Media sites Structure Mining of Social Media -- social network analysis of the node and connection (graph) structures underlying Social Media sites
In this paper, we are interested in using text mining to analyze textual data obtained from electronic social media in order to find out social concerns on crisis. In particular, we explore the temporal theme patterns in the natural catastrophe, i.e. the Yushu Earthquake, and compare the foci of the Chinese public, Chinese government and the overseas. By incorporating sources of information with a...
Web content clustering is very important part of topic detection and tracking issue. In our paper we focus on pre-processing phase of web content clustering. We focus on blog articles published in Slovak language. We evaluate the impact of different data pre-processing methods on success of blog clustering. We found out that applying various text data manipulation techniques in preprocessing can improve...
The 3 most important issues for anomaly detection based intrusion detection systems by using data mining methods are: feature selection, data value normalization, and the choice of data mining algorithms. In this paper, we study primarily the feature selection of network traffic and its impact on the detection rates. We use KDD CUP 1999 dataset as the sample for the study. We group the features of...
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