Framework and Taxonomy of Understanding Metaverse and a Case Study of AI-Driven and Digital Twin-Based Clothing Customization System
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 15429 LNCS, Page: 81-94
2025
- 4Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
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Conference Paper Description
This paper presents a comprehensive framework for understanding the Metaverse, which is initially conceptualized as a multidimensional, co-creative network built upon Web 3.0 technologies. The Metaverse promises a shift from transactional interactions to a collaborative ecosystem, integrating virtual and physical realms for richer, more immersive experiences. Through a case study of an AI-driven digital twin-based clothing customization system, the paper illustrates how these technologies eliminate the need for physical measurements, allowing users to remotely design and customize well-fitting garments. This study highlights the potential of such innovations to revolutionize virtual commerce, offering new business models and enhanced user experiences within the evolving Metaverse.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85210323203&origin=inward; http://dx.doi.org/10.1007/978-3-031-76977-1_6; https://link.springer.com/10.1007/978-3-031-76977-1_6; https://dx.doi.org/10.1007/978-3-031-76977-1_6; https://link.springer.com/chapter/10.1007/978-3-031-76977-1_6
Springer Science and Business Media LLC
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