Data-Driven Study on the Evolution of Forms and Types of Ancient Luoyang Coins
- DOI
- 10.2991/978-94-6463-276-7_43How to use a DOI?
- Keywords
- Ancient Luoyang coinage; Big data technologies; Data parsing; Cultural significance
- Abstract
This study delves into the evolution of ancient Luoyang coinage in terms of its forms and types. Leveraging big data technologies, the Selenium library combined with Python scripting was employed to drive web searches and capture data related to ancient Luoyang coins. Subsequently, the PyQuery library was utilized to parse search results and extract pertinent data. All retrieved data, such as casting epochs, shapes, and materials, underwent preprocessing and were stored in a MongoDB database, ensuring efficient querying capabilities. The systematic analytical framework guaranteed data integrity and precision. In-depth data analysis unveiled the coinage techniques behind ancient coins and their developmental trends across various historical epochs. Through this research, the historical and cultural significance of ancient Luoyang coins is further illuminated. The comprehensive application of big data technologies not only offers a fresh perspective on ancient Luoyang coins but also furnishes invaluable insights for interdisciplinary studies.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Pan Jing AU - Sastra Laoakka PY - 2023 DA - 2023/10/27 TI - Data-Driven Study on the Evolution of Forms and Types of Ancient Luoyang Coins BT - Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023) PB - Atlantis Press SP - 398 EP - 409 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-276-7_43 DO - 10.2991/978-94-6463-276-7_43 ID - Jing2023 ER -