基于LBSN用户生成短文本的细粒度位置推测技术

doi:10.11896/jsjkx.180901624

计算机科学 ›› 2019, Vol. 46 ›› Issue (10): 316-321.doi: 10.11896/jsjkx.180901624

基于LBSN用户生成短文本的细粒度位置推测技术

邓尧¹, 冀汶莉¹, 李勇军², 高兴¹

(西安科技大学通信与信息工程学院西安710054)¹
(西北工业大学计算机学院西安710072)²

收稿日期:2018-09-03 修回日期:2019-01-06 出版日期:2019-10-15 发布日期:2019-10-21
通讯作者: 李勇军(1973-),男,博士,副教授,主要研究方向为社交计算与社会网络,E-mail:lyj@nwpu.edu.cn。
作者简介:邓尧(1993-),男,硕士生,主要研究方向为自然语言处理;冀汶莉(1973-),女,硕士,副教授,主要研究方向为数据分析与挖掘;高兴(1994-),女,硕士生,主要研究方向为社交计算与社会网络。
基金资助:
本文受陕西省自然科学基础研究计划(2018JM6063)资助。

Fine-grained Geolocalisation of User Generated Short Text Based on LBSN

DENG Yao¹, JI Wen-li¹, LI Yong-jun², GAO Xing¹

(School of Communication and Information Engineering,Xi ’an University of Science and Technology,Xi’an 710054,China)¹
(School of Computer,Northwestern Polytechnical University,Xi’an 710072,China)²

Received:2018-09-03 Revised:2019-01-06 Online:2019-10-15 Published:2019-10-21

摘要/Abstract

摘要： 利用用户生成短文本(User Generated Short Text,UGST)推测用户的细粒度位置对基于位置服务的应用有重要的意义。现有的细粒度位置推测方法较少引入UGST中的语义信息,且未考虑UGST中语义实体的权重,因此性能较低。针对这些问题,提出了一种基于位置社交网络(Location-based Social Network,LBSN)的UGST细粒度位置推测方法。该方法包括如下3个过程:1)使用Foursquare中的UGST构建实体和位置之间的关联模型,以解决位置标记稀疏问题;2)判断待推测位置的UGST中是否含有位置信息,过滤不包含任何位置语义信息的UGST,以消除噪声短文本的干扰;3)根据UGST内容推测可能的候选位置,并对每个候选位置进行排名,选择排名最靠前的位置作为推测位置。实验结果验证了所提方法的有效性。

关键词: LBSN, 地理定位, 短文本, 位置推测, 细粒度

Abstract: It is significant to use user generated short text (UGST) to estimate user’s fine-grained location.Most exis-ting methods rarely introduce the semantic information about the location in UGST,and do not prioritize the entities according to their importance,thus leading to the decrease of performance.A fine-grained geolocalisation of user-generated short text based on location-based social network (LBSN) was proposed to solve these problems.The proposed algorithm consists of three key components.1) UGST of Foursquare is used to build the tight coupling between entity and location,which can address the location-annotated sparseness problem.2) UGST is filtered out if it does not contain any location-specific entities,which allows us to eliminate the interference of noisy UGSTs.3) The candidate locations for each remaining UGST are ranked based only on its textual data,and the top-ranked location is selected for UGST.The experimental results show the effectiveness of the proposed method.

Key words: Fine-grained, Geolocalisation, LBSN, Position estimation, Short text

中图分类号:

TP311

邓尧, 冀汶莉, 李勇军, 高兴. 基于LBSN用户生成短文本的细粒度位置推测技术[J]. 计算机科学, 2019, 46(10): 316-321. https://doi.org/10.11896/jsjkx.180901624

DENG Yao, JI Wen-li, LI Yong-jun, GAO Xing. Fine-grained Geolocalisation of User Generated Short Text Based on LBSN[J]. Computer Science, 2019, 46(10): 316-321. https://doi.org/10.11896/jsjkx.180901624

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基于LBSN用户生成短文本的细粒度位置推测技术

Fine-grained Geolocalisation of User Generated Short Text Based on LBSN

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