Special issue on big data research in China

Abstract

On March 5–7, 2013, the National Natural Science Foundation of China (NSFC) organized the 89th Shuangqing Forum in Tongji University (Shanghai, China) on “Challenging Scientific Problems in Big Data Technologies and Applications” [1]. Big data refers to dynamic information that is generated in complex systems and has the characteristics of huge quantity, continuous sampling, multiple sources, and sparse values [2]. Big data has attracted tremendous attention from academia, industry, and the government both within China and internationally. Big data research seeks to extract useful information from massive data and to use it to facilitate our decision making [3]. In the future, big data technologies are expected to make a full use of public data resources to realize digital and intelligent transformations in areas such as traffic management, logistics, health care, and education [4]. However, the research on big data technologies still has many challenges. Therefore, this Springer KAIS special issue invites original research work on Big Data in China from both the invited speakers from the above NSFC forum and other established researchers in this field. We aim to bring together innovative designs, revolutionary ideas, and emerging applications of big data efforts. For this special issue, from all invited and regular submissions, only ninewere accepted for publication. The first paper, by Xu et al., proposed an automatic annotating technique based on the analysis of streaming social interactions of media content. This method first iteratively loads the streaming records to build the preference-sensitive subgraphs, then extracts static