Diversified Trajectory Pattern Ranking in Geo-tagged Social Media
Diversified Trajectory Pattern Ranking in Geo-tagged Social Media
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DOI：
10.1137/1.9781611972818.84
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发表时间：
2011-12
期刊：
影响因子：
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通讯作者：
Zhijun Yin;Liangliang Cao;Jiawei Han;Jiebo Luo;Thomas S. Huang
中科院分区：
文献类型：
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作者：
Zhijun Yin;Liangliang Cao;Jiawei Han;Jiebo Luo;Thomas S. Huang
近年来，诸如驻留在流行的照片共享网站中的那些社交媒体吸引了越来越多的关注。作为一种用户生成的数据，群体智慧嵌入在这样的社交媒体中。特别是，数以百万计的用户将他们的照片上传到Flickr，其中许多照片与时间和地理信息有关。在本文中，我们研究了如何从上传的照片与地理标签和时间戳的轨迹模式进行排名。其主要目的是揭示集体智慧记录在看似孤立的照片和个人旅行序列所反映的地理标记的照片。我们没有专注于从地理标记的社交媒体中挖掘频繁的轨迹模式，而是将更多的精力放在对挖掘出的轨迹模式进行排名并使排名结果多样化上。通过利用用户、位置和轨迹之间的关系，我们对轨迹模式进行排名。然后，我们使用基于范例的算法来多样化的结果，以发现代表性的轨迹模式。我们已经评估了12个不同的城市使用Flickr数据集的建议框架，并证明了其有效性。
Social media such as those residing in the popular photo sharing websites is attracting increasing attention in recent years. As a type of user-generated data, wisdom of the crowd is embedded inside such social media. In particular, millions of users upload to Flickr their photos, many associated with temporal and geographical information. In this paper, we investigate how to rank the trajectory patterns mined from the uploaded photos with geotags and timestamps. The main objective is to reveal the collective wisdom recorded in the seemingly isolated photos and the individual travel sequences reflected by the geo-tagged photos. Instead of focusing on mining frequent trajectory patterns from geo-tagged social media, we put more effort into ranking the mined trajectory patterns and diversifying the ranking results. Through leveraging the relationships among users, locations and trajectories, we rank the trajectory patterns. We then use an exemplar-based algorithm to diversify the results in order to discover the representative trajectory patterns. We have evaluated the proposed framework on 12 different cities using a Flickr dataset and demonstrated its effectiveness.