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With the rapid development of big data analytics, mobile computing, Internet of Things, cloud computing, and social networking, cyberspace has expanded to a cross-fused and ubiquitous space made up of human beings, things, and information. Internet applications have evolved from Web 1.0 to Web 2.0 and Web 3.0, and web information has seen an explosive growth, which is strongly promoting the advent...
Topic detection and tracking (TDT) under modern media circumstances has been dramatically innovated with the ever-changing social network and inconspicuous connections among participants in the internet communities. Apart from the inherent word features of analysing materials, such as news articles and personal or professional comments, incidental information attracts increasing attention from the...
In this paper, we focus on distance-based outliers detection in an uncertain dataset, which is very useful in large social network. Based on the x-tuple model and the possible world semantics, we propose the concept of tuple outlier score, top k\ probability and top (k1, k2) distance-based outlier. We then design an algorithm using dynamic programming technique to calculate tuple outlier scores and...
Users can annotate themselves using free tags in micro-blogging website such as Sina Weibo. The tags of a user demonstrate the characteristics of the user and are generally in a random order without any importance or relevance information. It limits the effectiveness of user tags in system recommendation and other applications. In this paper, we proposed a user tag ranking schema which is based on...
The hidden knowledge in the information network has attracted a large number of researchers from different subjects such as sociology, physics and computer science. Community discovery has great significance for the analysis of information network structure, the understanding of its function, the discovery of its hidden patterns, and the predication of its behavior. In the practical life, people tend...
The hidden knowledge in the information network has attracted a large number of researchers from different subjects such as sociology, physics and computer science. Community discovery has great significance for the analysis of information network structure, the understanding of its function, the discovery of its hidden patterns, and the predication of its behavior. In the practical life, people tend...
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