Towards Spatial Word Embeddings

  • Paul MoussetEmail author
  • Yoann Pitarch
  • Lynda Tamine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11438)


Leveraging textual and spatial data provided in spatio-textual objects (eg., tweets), has become increasingly important in real-world applications, favoured by the increasing rate of their availability these last decades (eg., through smartphones). In this paper, we propose a spatial retrofitting method of word embeddings that could reveal the localised similarity of word pairs as well as the diversity of their localised meanings. Experiments based on the semantic location prediction task show that our method achieves significant improvement over strong baselines.


Word embeddings Retrofitting Spatial 



This research was supported by IRIT and ATOS Intégration research program under ANRT CIFRE grant agreement \(\#2016/403\).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.IRIT, Université de Toulouse, CNRSToulouseFrance
  2. 2.Atos IntégrationToulouseFrance

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