National Research Center of Fundamental Software, Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China;State Key Laboratory of Computer Science (Institute of Software, The Chinese Academy of Sciences), Beijing 100190, China 在期刊界中查找 在百度中查找 在本站中查找
Mining of the enclosed regions that are visited frequently by moving objects (i.e. hot region) is a critical premise for the discovery of movement patterns from trajectory databases, and restricting their coverage is the key to promote precision and efficiency for representation of trajectory patterns. Given a trajectory database, this paper studies how to discover these hot regions and how to constraint their size. A definition of hot region query with coverage constraints is presented with a filter-refinement framework to construct them. In the filter step, the study introduces a grid-based approximate schema to construction the dense regions efficiently; and in the refinement step, the study proposes two trend-based and dissimilarity-based measures, and designs corresponding algorithms and heuristic parameter selection method to rationally reconstruct the regions under the coverage constraints. Experiments on practical datasets validate the effectiveness of this work.