Keyword-aware Optimal Route Query (KOR) searches for an optimal route with the shortest traveling time under the conditions of full coverage of keywords and route budget, and is a high-frequency query in numerous map applications. Shortening the execution time is the significant goal of KOR optimization. The state-of-the-art algorithms primarily utilize various route expansion approaches to evaluate KORs, and focus on pruning strategies to reduce the search scale and shorten the execution time. Those strategies are effective in controlling the search scale for short routes, however, ineffective for long routes, because the search scale increases exponentially with the search depth. Therefore, this paper proposes PSE-KOR, a segmented parallel expansion algorithm for KOR, to address the issue for long routes. PSE-KOR constructs the routes with keyword vertexes as necessary passing nodes to satisfy the full coverage of keywords and budget, and divides the route into multiple segments taking the keyword vertexes as the boundary to limit the search scale and expands them in parallel to accelerate execution. For each route segment, a local budget limit pruning strategy is proposed to constrain the expansion direction and search depth, while reducing the interference among multiple segments. Extensive experiments verify the efficiency and effectiveness of PSE-KOR.

Keyword-aware Optimal Route Query (KOR) 在关键字和路线预算全覆盖的情况下搜索旅行时间最短的最优路线，是众多地图应用中的高频查询。缩短执行时间是 KOR 优化的重要目标。最先进的算法主要利用各种路由扩展方法来评估 KOR，并专注于修剪策略以减少搜索规模并缩短执行时间。这些策略对于控制短路径的搜索规模是有效的，但是对于长路径是无效的，因为搜索规模随着搜索深度呈指数增长。因此，本文提出了PSE-KOR，一种用于KOR的分段并行扩展算法，以解决长路由问题。PSE-KOR构建以关键字顶点为必经节点的路由以满足关键字和预算的全覆盖，并以关键字顶点为边界将路由分成多段限制搜索规模并并行扩展加速执行. 对于每个路段，提出了一种局部预算限制剪枝策略来约束扩展方向和搜索深度，同时减少多个路段之间的干扰。大量实验验证了 PSE-KOR 的效率和有效性。提出了一种局部预算限制剪枝策略来约束扩展方向和搜索深度，同时减少多个段之间的干扰。大量实验验证了 PSE-KOR 的效率和有效性。提出了一种局部预算限制修剪策略来约束扩展方向和搜索深度，同时减少多个段之间的干扰。大量实验验证了 PSE-KOR 的效率和有效性。