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多用户移动顺序推荐：一种高效的并行计算模式

Multi-User Mobile Sequential Recommendation: An Efficient Parallel Computing Paradigm
课程网址: http://videolectures.net/kdd2018_ye_mobile_sequential_recommendat...  
主讲教师: Zeyang Ye
开课单位: 石溪大学
开课时间: 2018-11-23
课程语种: 英语
中文简介:
经典的移动顺序推荐（MSR）问题旨在为出租车司机提供最佳路线，以在他们遇到下一位乘客之前最小化潜在的旅行距离。然而，该问题是从单个用户的角度设计的，可能导致重叠的推荐并导致交通问题。现有的方法通常包含离线修剪过程，考虑到大量的拾取点，该过程具有极高的计算成本。为此，我们形式化了一个新的多用户MSR（MMSR）问题，该问题为一组具有不同起始位置的驾驶员定位最优路线。我们开发了两种有效的方法，PSAD和PSAD-M，用于通过组合并行计算和模拟退火来解决MMSR问题。我们的方法优于现有的几种方法，尤其是在高维MMSR问题上，使用384个内核的速度提高了180倍，创纪录。
课程简介: The classic mobile sequential recommendation (MSR) problem aims to provide the optimal route to taxi drivers for minimizing the potential travel distance before they meet next passengers. However, the problem is designed from the view of a single user and may lead to overlapped recommendations and cause traffic problems. Existing approaches usually contain an offline pruning process with extremely high computational cost, given a large number of pick-up points. To this end, we formalize a new multi-user MSR (MMSR) problem that locates optimal routes for a group of drivers with different starting positions. We develop two efficient methods, PSAD and PSAD-M, for solving the MMSR problem by ganging parallel computing and simulated annealing. Our methods outperform several existing approaches, especially for high-dimensional MMSR problems, with a record-breaking performance of 180x speedup using 384 cores.
关 键 词: 经典的移动顺序推荐; 推荐并导致交通问题; 解决MMSR问题; 租车司机提供最佳路线
课程来源: 视频讲座网
数据采集: 2023-03-08：cyh
最后编审: 2023-03-08：cyh
阅读次数: 15

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