Generative AI in Graph-Based Spatial Computing: Techniques and Use Cases

Sankara Reddy Thamma

International Journal of Scientific Research in Science and Technology, 2024, vol. 11, issue 2, 1012-1023

Abstract: Generative AI has proven itself as an efficient innovation in many fields including writing and even analyzing data. For spatial computing, it provides a potential solution for solving such issues related to data manipulation and analysis within the spatial computing domain. This paper aims to discuss the probabilities of applying generative AI to graph-based spatial computing; to describe new approaches in detail; to shed light on their use cases; and to demonstrate the value that they add. This technique thus incorporates graph theory, generative models to model spatial relations, generate new spatial forms and improve on spatial decision-making processes. The paper surveys such methods, describes typical applications, and outlines further development of the subject.

Keywords: Generative AI; Spatial Computing; Graph-Based Computing; Graph Theory; Spatial Data Modeling; AI Techniques; Machine Learning; Predictive Models; Geospatial Applications; Graph Neural Networks (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v11:y2024:i2:id:545

DOI: 10.32628/IJSRST24112135

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