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PATS: A Framework of Pattern-Aware Trajectory Search

机译:PATS:模式识别轨迹搜索框架

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In this paper, we develop a framework of trajectory search called pattern-aware trajectory search abbreviated as PATS). Given a set of trajectories, potential regions are extracted first and potential regions are viewed as popular regions interested by users. Furthermore, potential regions are organized as a region transition graph where each vertex is a potential region and edges capture sequential travels of potential regions from a set of trajectories given. By exploring the concept of random walk, the attractiveness of a potential region is derived. In light of attractiveness of potential regions the attractiveness of a trajectory is formulated and PATS will return top-K trajectories according to their attractiveness. We evaluated our framework by a real GPS dataset. Experimental results show that PATS is able to retrieve trajectories interested by users.
机译:在本文中,我们开发了一种轨迹搜索框架,称为模式感知轨迹搜索(缩写为PATS)。给定一组轨迹,首先提取潜在区域,并将潜在区域视为用户感兴趣的流行区域。此外,潜在区域被组织为区域过渡图,其中每个顶点都是一个潜在区域,并且边缘从给定的一组轨迹中捕获潜在区域的顺序行进。通过探索随机行走的概念,可以得出潜在区域的吸引力。鉴于潜在区域的吸引力,制定了轨迹的吸引力,PATS将根据其吸引力返回前K个轨迹。我们通过一个真实的GPS数据集评估了我们的框架。实验结果表明,PATS能够检索用户感兴趣的轨迹。

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