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

Autor:	Arslan, Muhammad, Cruz, Christophe
Rok vydání:	2023
Předmět:	Computer Science - Information Retrieval Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: Presented in the conference Spatial Analysis and GEOmatics 2023 SAGEO
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.10034 Zobrazit plný text záznamu View this record from Arxiv