The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue that an essential feature for such agents is the capability to analyse data and learn. In this paper we outline the challenges and issues surrounding the application of clustering algorithms to Semantic Web data. We present seve...

The ever severe dynamic competitive environment has led to increasing complexity of strategic decision making in giant organizations. Strategy formulation is one of basic processes in achieving long range goals. Since, in ordinary methods considering all factors and their significance in accomplishing individual goals are almost impossible. Here, a new approach based on clustering method is pro...

Instance segmentation is an important pre-processing task in numerous real-world applications, such as robotics, autonomous vehicles, and human–computer interaction. Compared with the rapid development of deep learning for two-dimensional (2D) image tasks, learning-based instance 3D point cloud still has a lot room development. In particular, distinguishing large number occluded objects same cl...

Computer vision enables the development of new approaches to monitor behavior, health, and welfare animals. Instance segmentation is a high-precision method in computer for detecting individual animals interest. This can be used in-depth analysis animals, such as examining their subtle interactive behaviors, from videos images. However, existing deep-learning-based instance methods have been mo...