CAJ | 학술논문

　　发现被移动对象频繁造访的热门区域是从轨迹数据库中挖掘运动模式的重要前提，而合理约束热门区域的大小是提高轨迹模式的精确表达能力的关键。研究如何从轨迹数据库找出热门区域及如何限制其大小。定义了带有覆盖范围约束的热门区域，并采用过滤-精炼策略发现热门区域。在过滤阶段，设计了一种基于网格的密集区域发现近似算法以提高发现效率；在精炼阶段，提出了基于趋势和差异性的度量指标，实现了对应区域重构算法及重构参数启发性选择算法，保证了从密集区域中有效提取出符合覆盖范围约束的热门区域。在真实数据集上验证了该工作的有效性。
　　발현피이동대상빈번조방적열문구역시종궤적수거고중알굴운동모식적중요전제，이합리약속열문구역적대소시제고궤적모식적정학표체능력적관건。연구여하종궤적수거고조출열문구역급여하한제기대소。정의료대유복개범위약속적열문구역，병채용과려-정련책략발현열문구역。재과려계단，설계료일충기우망격적밀집구역발현근사산법이제고발현효솔；재정련계단，제출료기우추세화차이성적도량지표，실현료대응구역중구산법급중구삼수계발성선택산법，보증료종밀집구역중유효제취출부합복개범위약속적열문구역。재진실수거집상험증료해공작적유효성。
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.