互动式行程规划

Senjuti Basu Roy, Gautam Das, S. Amer-Yahia, Cong Yu
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引用次数: 76

摘要

在城市旅行时,规划行程涉及到大量的工作,包括选择兴趣点(POI),决定访问它们的顺序,以及考虑访问每个POI和在它们之间中转所需的时间。一些在线服务解决了行程规划的不同方面,但它们都没有提供一个交互式界面,用户可以根据个人兴趣和时间预算来反馈和迭代地构建行程。在本文中,我们将交互式行程规划形式化为一个迭代过程,在每个步骤中:(1)用户对系统选择的poi提供反馈,(2)系统根据迄今为止的所有反馈推荐最佳行程,(3)系统进一步选择一组具有最佳效用的新poi,以便在下一步征求反馈。当用户对推荐的行程感到满意时,此迭代过程停止。我们证明了即使对于简单的行程评分函数,计算行程也是np完全的,并且POI的选择也是np完全的。我们针对一个特定的情况开发了启发式和优化,其中行程的分数与它包含的期望poi的数量成正比。我们的大量实验表明,我们的算法是有效的,并返回高质量的行程。
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Interactive itinerary planning
Planning an itinerary when traveling to a city involves substantial effort in choosing Points-of-Interest (POIs), deciding in which order to visit them, and accounting for the time it takes to visit each POI and transit between them. Several online services address different aspects of itinerary planning but none of them provides an interactive interface where users give feedbacks and iteratively construct their itineraries based on personal interests and time budget. In this paper, we formalize interactive itinerary planning as an iterative process where, at each step: (1) the user provides feedback on POIs selected by the system, (2) the system recommends the best itineraries based on all feedback so far, and (3) the system further selects a new set of POIs, with optimal utility, to solicit feedback for, at the next step. This iterative process stops when the user is satisfied with the recommended itinerary. We show that computing an itinerary is NP-complete even for simple itinerary scoring functions, and that POI selection is NP-complete. We develop heuristics and optimizations for a specific case where the score of an itinerary is proportional to the number of desired POIs it contains. Our extensive experiments show that our algorithms are efficient and return high quality itineraries.
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