基于EBSN的效用时间社会事件策划

Linlin Ding, Hanlin Zhang, Ze Chen, Baoyan Song
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引用次数: 0

摘要

目前,基于事件的社交网络(EBSN)平台越来越受欢迎,其主要功能是为感兴趣的用户安排合适的社交活动。现有的方法通常假设每个用户可以参与有限数量的事件,并解决由有限数量的事件引起的时空冲突。然而,在实际应用中,现有的方法存在以下问题:(1)没有估算出行距离造成的时间成本;(2)限制用户参与事件数量和用户日程安排的约束不够准确。因此,首先,我们结合位置信息,提出RDP算法,在综合考虑用户空闲时间、用户平均移动速度、用户整体兴趣值的基础上,提供个性化的活动策划,保证了我们算法的近似比值。其次,提出RGPV和RGPT算法,减少运行时间,提高时间和空间效率,保证每个用户都能按时参与到事件中。最后,基于真实数据集的实验验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utility-Time Social Event Planning on EBSN
At present, event-based social network (EBSN) platforms are becoming more and more popular, which main function is to arrange appropriate social activities for interested users. The existing methods usually assume that each user can participate in a limited number of events and solve the spatio-temporal conflicts caused by the limited number of events. However, in practical applications, the existing methods emerge the following problems: (1) they don't estimate the time cost caused by travel distance; (2) the constraint of the limiting number of users participating events and the schedule of users is not accurate enough. Therefore, first, we combine the position information and propose RDP algorithm to provide personalized event planning based on considering the free time of users, the average moving speed of users, the interest value of users as a whole, which ensures the approximate ratio of our algorithm. Second, we present RGPV and the RGPT algorithms to reduce the running time and improve the efficiency of time and space, so as to ensure each user can participate in the events on time. Finally, the experiments based on the real dataset can show that the proposed algorithms are effective and efficient.
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