当今社会的发展和技术的快速进步增加了对实时获取动态、适用和个性化信息的需求。增强现实可对高速流动的信息进行快捷访问，而当这些信息被嵌入适当的空间和时间框架时，也会变得更有意义和更为生动。增强现实为用户与物理和数字世界进行实时交互提供了新的方法。此外，日常生活的数字化导致数据量呈指数级增长，在引发新的需求和挑战的同时也带来了新的机遇和可能性。
知识图谱和语义网络技术利用数据的增长和网络内容的表示来提供语义上相互关联的信息，而深度学习技术则在多个领域提供了新颖的解决方案和应用。
本文研究的目的是展示增强现实与深度学习、语义网络和知识图谱的集成如何扩展了它的功能和服务，并展示这种结合在开发现代的、用户友好的和以用户为中心的智能应用中的潜力。
我们简述了增强现实和混合现实的概念，并介绍了深度学习、语义网络和知识图谱技术；基于文献综述，介绍和分析了运用这些技术开发增强现实应用和系统的相关研究。我们展示了深度学习、语义网络和知识图谱与增强现实的集成怎样提升增强现实应用的体验质量和服务质量，从而便利和改善了用户的日常生活。最后为未来研究提供了结论与建议。
关键词: 增强现实，机器学习，深度学习，语义网络， 知识图谱，人机交互
全文信息
Enhancing the functionality of augmented reality using deep learning, semantic web and knowledge graphs: A review
BY: Georgios Lampropoulos, Euclid Keramopoulos, Konstantinos Diamantaras
Abstract:
The growth rates of today’s societies and the rapid advances in technology have led to the need for access to dynamic, adaptive and personalized information in real time. Augmented reality provides prompt access to rapidly flowing information which becomes meaningful and “alive” as it is embedded in the appropriate spatial and time framework. Augmented reality provides new ways for users to interact with both the physical and digital world in real time. Furthermore, the digitization of everyday life has led to an exponential increase of data volume and consequently, not only have new requirements and challenges been created but also new opportunities and potentials have arisen. Knowledge graphs and semantic web technologies exploit the data increase and web content representation to provide semantically interconnected and interrelated information, while deep learning technology offers novel solutions and applications in various domains. The aim of this study is to present how augmented reality functions and services can be enhanced when integrating deep learning, semantic web and knowledge graphs and to showcase the potentials their combination can provide in developing contemporary, user-friendly and user-centered intelligent applications. Particularly, we briefly describe the concept of augmented reality and mixed reality and present deep learning, semantic web and knowledge graphs technologies. Moreover, based on our literature review, we present and analyze related studies regarding the development of augmented reality applications and systems that utilize these technologies. Finally, after discussing how the integration of deep learning, semantic web and knowledge graphs into augmented reality enhances the quality of experience and quality of service of augmented reality applications to facilitate and improve users’ everyday life, conclusions and suggestions for future research and studies are given.
Keywords: Augmented reality, Machine learning, Deep learning, Semantic web, Knowledge graph, Human computer interaction
Link: https://www.sciencedirect.com/science/article/pii/S2468502X20300012（点击链接，免费下载全文。）
期刊信息
Visual Informatics（中文名《可视信息学》）是由浙江大学主办、浙江大学出版社和Elsevier出版集团联合出版、在线发行、开放获取的国际学术期刊。该刊聚焦于面向人类感知的视觉信息的建模、分析、合成、增强与自然交互。主编是周昆教授、Hans-Peter Seidel教授。
Elsevier link (including First Online Articles): https://www.journals.elsevier.com/visual-informatics
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