利用微博文本和友情进行位置推断

Chuanyang Li, Xiuqin Lin, Bin Wu, C. Shi
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引用次数: 0

摘要

在本文中,我们提出了一种新的方案,利用微博文本和友谊来推断用户的位置,而不需要已知的地理信息。我们研究的主要部分是识别与特定地点相关的当地词汇。对于我们识别的本地词,我们使用条件随机场(CRF)来检测特定位置的微博。然后我们可以估计出用户最可能的位置。我们利用用户的友谊来改善结果。我们的方法的另一个关键特征是我们考虑了本地词的时效性,因为一些本地词是对本地事件的描述,它们只与特定时间段内的位置相关联。实验表明,该算法在实际应用中效果良好,优于现有的微博用户位置估计算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Location inference using microblog text and friendships
In this paper, we proposed a novel scheme to infer user's location using microblog text and friendships, without known geo information. The major part of our research is identifying local words, words that associated with some particular location. With local words we identified, we use conditional random fields (CRF), to detect location specific microblog. Then we can estimate the most possible location of a user. And we take advantage of users' friendships to improve the result. Another key feature of our approach is that we consider timeliness of local words, as some local words are descriptions of local events and they are only associated with location during a certain period of time. Experimental evidence suggests that our algorithm works well in practice and outperforms the existing algorithms for estimating the location of microblog users.
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