Computer Science

Computer Science ›› 2019, Vol. 46 ›› Issue (10): 316-321.doi: 10.11896/jsjkx.180901624

• Interdiscipline & Frontier • Previous Articles     Next Articles

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

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

  1. (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

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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

CLC Number: 

  • TP311
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