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Recent years have witnessed the explosive growth of online social media. Weibo, a Twitter-like online social network in China, has attracted more than 300 million users in less than three years, with more than 1000 tweets generated in every second. These tweets not only convey the factual information, but also reflect the emotional states of the authors,(More)
K-means is a widely used partitional clustering method. While there are considerable research efforts to characterize the key features of K-means clustering, further investigation is needed to reveal whether and how the data distributions can have the impact on the performance of K-means clustering. Indeed, in this paper, we revisit the K-means clustering(More)
Clustering validation has long been recognized as one of the vital issues essential to the success of clustering applications. In general, clustering validation can be categorized into two classes, external clustering validation and internal clustering validation. In this paper, we focus on internal clustering validation and present a detailed study of 11(More)
MicroRNAs (miRNA) are small regulatory RNAs that control gene expression by translational suppression and destabilization of target mRNAs. There is increasing evidence that miRNAs regulate genes associated with fibrosis in organs, such as the heart, kidney, liver, and the lung. In a large-scale screening for miRNAs potentially involved in bleomycin-induced(More)
Architectural style classification differs from standard classification tasks due to the rich inter-class relationships between different styles, such as re-interpretation, revival, and territoriality. In this paper, we adopt Deformable Part-based Models (DPM) to capture the morphological characteristics of basic architectural components and propose(More)
BACKGROUND INFORMATION Although the mechanism of cementogenesis is an area full of debate, the DFCs (dental follicle cells) are thought to be the precursors of cementoblasts. At the onset of cementogenesis, DFCs come into contact with the root dentin surface and undergo subsequent differentiation. But the exact effects of dentin or dentin matrix on DFCs(More)
K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for k-means. However, the common characteristics of proximity functions remain unknown. To this end, in this paper, we show that all proximity functions that fit k-means clustering can be generalized as k-means(More)