随着人们对高效、个性化服务的日益关注,其对旅游规划的要求也越来越高.然而,目前制定一个完美的、个性化的旅游规划很困难.一个合理的旅游规划应该包含以下特征:1)基于游客兴趣爱好的个性化推荐;2)覆盖尽可能多的兴趣景点;3)走最少的路程,花费最少的时间.由于每次旅游包含多个景点,因此该问题变成了每个景点都附有权值的时空序列优化问题.为了实现最优个性化旅游规划,首先,针对每个城市为每位游客提供一系列带有权值的景点;然后,综合考虑距离、权值、旅游时间和景点特色等因素,为游客推荐一个最优旅游序列.为此,提出了4种有效算法,使游客在旅游时间范围限制内走最少的路程来游览最想游览的景点.在社交网络的真实数据集上,通过实验验证了所提算法的有效性.%Nowadays,due to the increasing user requirements of efficient and personalized services,a perfect trip planning is urgently needed.However,it is hard for people to make a personalized traveling plan at present.For a satisfactory trip planning,the following features are desired:i) personalized recommender based on the interest and habits of travelers;ii) maximal coverage of sites of interest;iii) minimal effort such as transporting time on the route.As a trip contains a sequence of stops at multiple scenes,the problem of trip planning becomes an optimized spatio-temporal sequence where each stop is weighted.For each city,this paper generated a set of weighted scenes for each user.Then it can retrieve the optimal sequence of scenes in terms of distance,weight,visiting time and scene features.We developed alternative algorithms for searching optimal sequences,with consideration of the weight of each scene,the preference of users,and the travel time constraint.The experiments demonstrate the efficiency of the proposed algorithms based on real datasets from social networks.
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