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Unlocking Insights into Business Trajectories with Transformer-based Spatio-temporal Data Analysis

Information Retrieval 2023-06-21 v1 Machine Learning
Authors: Muhammad Arslan , Christophe Cruz
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Abstract

The world of business is constantly evolving and staying ahead of the curve requires a deep understanding of market trends and performance. This article addresses this requirement by modeling business trajectories using news articles data.

Keywords

news recommendation data warehousing information modeling

Cite

@article{arxiv.2306.10034,
  title  = {Unlocking Insights into Business Trajectories with Transformer-based Spatio-temporal Data Analysis},
  author = {Muhammad Arslan and Christophe Cruz},
  journal= {arXiv preprint arXiv:2306.10034},
  year   = {2023}
}

Comments

Presented in the conference Spatial Analysis and GEOmatics 2023 SAGEO

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