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The advent of the era of Big Data has spawned a new research paradigm and has transformed the outlook of numerous fields in science and engineering. Similarly, as one of the important fields of safety science, the area of accident investigation also has great opportunities for leveraging Big Data to its advantage. With this in mind, in this article, the influencing factors of accident investigation...
Clustering has become an unavoidable step in big data analysis. It may be used to arrange data into a compact format, making operations on big data manageable. However, clustering of big data requires not only the capability of handling data with large volume and high dimensionality, but also the ability to process streaming data, all of which are less developed in most current algorithms. Furthermore,...
A person is considered as an influential individual when his behaviors can trigger other people's reactions. Such phenomenon is called user influence in social networks. Measuring user influence provides insights into dynamics of social network interactions. This makes a fundamental step for constructing marketing strategy, recommendation systems and so on. There have been various studies focusing...
Social media has been an important way for people to get news. It is designed to make the sharing of messages very fast and easy. It also attracted the attention of a large number of researchers. There has been research concerning predicting what messages will be popular. But it lacks of in-depth study of what features play an important role in the prediction task. In the work, we systematically and...
MPI has been widely used in High Performance Computing. In contrast, such efficient communication support is lacking in the field of Big Data Computing, where communication is realized by time consuming techniques such as HTTP/RPC. This paper takes a step in bridging these two fields by extending MPI to support Hadoop-like Big Data Computing jobs, where processing and communication of a large number...
Clustering is an important preparation step in big data processing. It may even be used to detect redundant data points as well as outliers. Elimination of redundant data and duplicates can serve as a viable means for data reduction and it can also aid in sampling. Visual feedback is very valuable here to give users confidence in this process. Furthermore, big data preprocessing is seldom interactive,...
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