Abstract. We propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem in Euclidean spaces. Compared to the limitations of existing methods for ...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Abstract: Efficient content-based similarity search in large multimedia databases requires efficient query processing algorithms for many practical applications. Especially in hi...
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Complex social and information network search becomes important with a variety of applications. In the core of these applications, lies a common and critical problem: Given a labe...
Arijit Khan, Nan Li, Xifeng Yan, Ziyu Guan, Supriy...