| id |
caadria2024_539 |
| authors |
Wang, Xiao, Zhu, Xuerong and Tang, Peng |
| year |
2024 |
| title |
Characterization of the Chinese Traditional Villages Based on the Morphological Clustering and Knowledge Graph |
| source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 263–272 |
| doi |
https://doi.org/10.52842/conf.caadria.2024.2.263
|
| summary |
The traditional settlements including Chinese traditional villages are facing the challenges posed by the digital divide in rural areas, which lack open-source data and comprehensive design. To address this, the study conducts an association analysis using morphological clustering and knowledge graphs, aiming to uncover the intrinsic logic and connections between tangible and intangible factors of village morphology. A comprehensive dataset of 8155 traditional villages, including geographical and morphological features, was compiled, supplemented with additional data on 1023 villages covering both tangible and intangible attributes. The methodology involves feature vector extraction using pre-trained neural networks, dimension reduction, and cluster analysis. Additionally, a graph database of village knowledge graph was established to identify entities and relationships, with visualization facilitated by the Neo4j. This research provides a method for analysing the characteristics of traditional villages, offering insights into their development trends and contributing to the formulation of globally applicable conservation and sustainable strategies in the era of artificial intelligence and climate change. |
| keywords |
traditional villages, knowledge graph, clustering, feature vectors, machine learning |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (5,485,252 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/11/17 22:05 |
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