1) 定义什么样的Region是用户最满意的Region，
2）利用1）中的定义，加上Region划分，搜索最佳region进行推荐
3）并没有考虑用户当前需求
| 文献题目 | 去谷歌学术搜索 | ||||||||||
| A General Model for Out-of-town Region Recommendation | |||||||||||
| 文献作者 | Tuan-Anh Nguyen Pham | ||||||||||
| 文献发表年限 | 2017 | ||||||||||
| 文献关键字 | |||||||||||
| Location-based social networks; region recommendation; out- of-town recommendation | |||||||||||
| 摘要描述 | |||||||||||
| With the rapid growth of location-based social networks (LBSNs), it is now available to analyze and understand user mobility behavior in real world. Studies show that users usually visit nearby points of interest (POIs), located in small regions, especially when they travel out of their hometowns. However, previous out-of-town recommendation systems mainly focus on recommending individual POIs that may reside far from each other, which makes the recommendation results less useful. In this paper, we introduce a novel problem called Region Recommendation, which aims to recommend an out-of-town region of POIs that are likely to be visited by a user. The proximity characteristic of user mobility behavior implies that the probability of visiting one POI depends on those of nearby POIs. Thus, to make accurate region recommendation, our proposed model exploits the influence between POIs, instead of treating them individually. Moreover, to overcome the efficiency problem of searching the best region, we propose a sweeping line-based method, and subsequently a constant-bounded algorithm for better efficiency. Experiments on two real-world datasets demonstrate the improved effectiveness of our models over baseline methods and efficiency of the approximate algorithm. | |||||||||||
