空间多样化约束下的移动k近邻查询

考虑为移动中的查询对象连续返回k个距离近并且满足空间多样化约束的对象，提出了空间多样化约束下的移动k近邻(SDC-MkNN)查询.在此，满足空间多样化约束代表对象之间的相互距离大于距离阈值.为了高效处理SDC-MkNN查询问题，提出了两种基于安全区域技术的算法.算法均通过减少重新计算查询结果的次数来提高查询效率.其中一种为精确算法EA，可连续返回精确的查询结果；另一种为近似算法ρAA，可连续返回具有近似率保障的近似查询结果.采用真实数据集验证了所提出算法的有效性.

Moving k Nearest Neighbor Query with Spatial Diversity Constraints

A new type of queries， named moving k nearest neighbor query with spatial diversity constraints(SDC-MkNN)， was proposed.When the query object is moving， this type of queries can continuously return the k nearest neighbors， and any two of the returned objects are satisfied with the spatial diversity constraints， which means the spatial distance between any two of the returned objects must be larger than the distance threshold.Based on the safe region technique， two algorithms were proposed to increase the query efficiency by reducing the frequency of the recomputation of query results.One is an exact algorithm(EA)， which can continuously return exact query results， and the other is an approximate algorithm(ρAA)， which can continuously return approximate query results with exact bounds.The proposed algorithms were verified by extensive experiments on a real dataset.The results confirm the superiority of the proposed algorithms over the baseline algorithm.