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DOI:
Journal of Software:2012.23(zk1):159-168

基于物理轨迹数据和社会网络的泛化行程推荐
孟祥旭,王晓东,周兴铭
(并行与分布处理国家重点实验室(国防科学技术大学 计算机学院),湖南 长沙 410073)
Intention Oriented Itinerary Recommendation by Bridging Physical Trajectories and Online Social Networks
MENG Xiang-Xu,WANG Xiao-Dong,ZHOU Xing-Ming
(National Key Laboratory of Parallel and Distributed Processing (College of Computer Science, National University of Defense Technology), Changsha 410073, China)
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Received:May 05, 2012    Revised:August 17, 2012
> 中文摘要: 人类活动行程的制定往往基于宽泛的最初意向,通过综合考虑各种约束条件加以优化而完成.当前,基于位置点名称查找的行程制定方法,不支持用户一次性提交多个具有时序关系的宽泛出行意向,更不能同时为多个地理位置点提供详细的最优驾车方案.基于位置社交网络信息和车辆历史轨迹数据,探索了支持用户多个模糊意向输入的泛化行程推荐框架,主要工作包括:(1) 对泛化的行程推荐问题进行建模;(2) 设计并实现了基于分类树的地理位置点(POI)查询策略和算法;(3) 提出了基于Voronoi 图的GPS 轨迹分析模型,并实现了任意两个位置点间最优行驶路径计算方法;(4) 联合社会网络和语义交通信息图,基于蚁群算法进行行程的推荐,并实现了原型系统.实验及问卷调查结果表明,推荐结果的用户满意度可达80%.
Abstract:Human itineraries are often initiated by some general intentions and will be optimized after considering all kinds of constraints and available information. This paper proposes a category-based itinerary recommendation framework to help the user transfer from intentions to itinerary planning, which join physical trajectories and information of location based social networks. The main contributions are: (1) Build the category based activity scheduling model; (2) Design and implement the category tree based POI (point or interest) query strategy and algorithm; (3) Propose the Voronoi graph based GPS trajectory analysis method to build traffic information networks; (4) Combine social networks with traffic information networks to implement category based recommendation by ant colony algorithm. The study conducts experiments on datasets from FourSquare and GeoLife project. A test on satisfaction of recommended items is also performed. Results show that the satisfaction reaches 80% in average.
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基金项目:国家自然科学基金(61170260) 国家自然科学基金(61170260)
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孟祥旭,王晓东,周兴铭.基于物理轨迹数据和社会网络的泛化行程推荐.软件学报,2012,23(zk1):159-168

MENG Xiang-Xu,WANG Xiao-Dong,ZHOU Xing-Ming.Intention Oriented Itinerary Recommendation by Bridging Physical Trajectories and Online Social Networks.Journal of Software,2012,23(zk1):159-168