Shuliang Wang

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Data mining environment produces a large amount of data, that need to be analyzed, patterns have to be extracted from that to gain knowledge. In this new era with boom of data both structured and unstructured, in the field of genomics, meteorology, biology, environmental research and many others, it has become difficult to process, manage and analyze(More)
A growing attention has been paid to spatial data mining and knowledge discovery (SDMKD). This paper presents the principles of SDMKD, proposes three new techniques, and gives their applicability and examples. First, the motivation of SDMKD is briefed. Second, the intension and extension of SDMKD concept are presented. Third, three new techniques are(More)
Recently, large data sets of protein-protein interactions (PPI) which can be modeled as PPI networks are generated through high-throughput methods. And locally dense regions in PPI networks are very likely to be protein complexes. Since protein complexes play a key role in many biological processes, detecting protein complexes in PPI networks is one of(More)
Shuliang Wang, Dakui Wang, Caoyuan Li, Yan Li School of software, Beijing Institute of Technology, Beijing, China International School of Software, Wuhan University, Wuhan, China Email: slwang2011@bit.edu.cn Abstract. In [1], a clustering algorithm was given to find the centers of clusters quickly. However, the accuracy of this algorithm heavily depend on(More)
Recommender system is an important content in the research of E-commerce technology. Collaborative filtering recommendation algorithm has already been used successfully at recommender system. However, with the development of E-commerce, the difficulties of the extreme sparsity of user rating data have become more and more severe. Based on the traditional(More)