Holographic communication is considered one of the typical scenarios in the 6G era. Studies have shown that the light field display is considered the most effective naked-eye 3D display method in the 6G era. Despite this, there are still many issues worthy of study. Since there are currently no experience-evaluation standards for holographic communications proposed worldwide, this also causes a lot of research work to remain at the design level and vision. To truly realize the holographic communication scenario, it is necessary to systematically evaluate the light field display technology. The level of user experience determines the value of the holographic communication scenario. This requires quantifying the user’s experience level and mapping it to the technical parameters of the light field display image. However, there is still room for improvement in related research. This paper proposes a model based on semi-supervised learning, which takes light field image data of various scenes as input and uses three experience scores of comfort, space, and realism as output to complete the subjective experience evaluation of light field images. Compared with evaluation methods that focus on the quality of the image itself, this article focuses more on the effect on human experience. Compared with existing work, this paper makes improvements in two respects: feature engineering and training strategies. In terms of feature selection, the convolutional neural network is used to extract image content features, and the image quality parameter-extraction module is used to extract image property features. The two are spliced as the input of the classifier; in terms of the training strategy, pseudo-labels and dynamic thresholds are used for training. The final experimental results show that on the MPI-LFA data set, the comfort dimension’s classification accuracy is 80.21, the spatial dimension’s classification accuracy is 83.12, and the realism dimension’s classification accuracy is 81.88.

At present, many metrics for 3D visual perception quality of light field images (LFIs) come from studies in the evaluation of traditional stereoscopic display or 2D display. Since these metrics do not take into account the optical display principle of the light field, their correlation with the subjective evaluation of LFIs is often weak. To address this problem, this study designed a new objective evaluation metric for the LFI—Density of perceptible viewpoints (DPV), which reflects the number of perceptible viewpoints at a certain observation angle. The performance differences between DPV and PSNR and SSIM are further compared based on the evaluation experiments of six light field scenes. The results show that the new metric has better correlation than PSNR and SSIM in reflecting the 3D visual perception quality of the human eye for LFI. Finally, a classification of 3D visual experience based on DPV is made in order to apply DPV.

A methodology is proposed to introduce knowledge graphs into the study of the Chinese cultural field for use in a newly designed, complete application. At present, the combination of culture and information technology has become a trend. Among various technologies, knowledge graphs are a very promising option. The contributions of this paper are as follows: it supplies for the first time a knowledge graph in the cultural field of the ancient capital of Beijing, establishes a domain knowledge base, and develops a platform for visual analysis and interactive question and answer. In this process, a framework for applying knowledge graphs to research in the cultural field is summarized, providing ideas for research in the cultural field.

As a combination of information computing technology and the cultural field, cultural computing is gaining more attention. The knowledge graph is also gradually applied as a particular data structure in the cultural area. Based on the domain knowledge graph data of the Beijing Municipal Social Science Project "Mining and Utilization of Cultural Resources in the Ancient Capital of Beijing," this article proposes a graph representation learning model CR-TransR that integrates cultural attributes. Through the analysis of the data in the cultural field of the ancient capital of Beijing, a cultural feature dictionary is constructed, and a domain-specific feature matrix is constructed in the form of word vector splicing. The feature matrix is used to constrain the embedding graph model TransR, and then the feature matrix and the TransR model are jointly trained to complete the embedded expression of the knowledge graph. Finally, a comparative experiment is carried out on the Beijing ancient capital cultural knowledge graph dataset and the effects of the classic graph embedding algorithms TransE, TransH, and TransR. At the same time, we try to reproduce the embedding method with the core idea of neighbor node information aggregation as the core idea, and CRTransR are compared. The experimental tasks include link prediction and triplet classification, and the experimental results show that the CRTransR model performs better.

关于6G的讨论已在全球范围内展开,明确未来的应用场景将为6G的建设与应用提供参考.研究显示,6G的发展不仅面临技术问题,还面临很多非技术因素,主要涉及行业壁垒、频谱分配、应用场景和政策法规等.采用遗传算法的思想,提出了一种在6G时代,从技术角度挖掘应用场景的方法,尝试解决6G发展面临的非技术挑战之一——应用场景.首先,基于人类社会发展规律的理论研究确定场景的组成要素为技术+需求;其次,分别对两者进行了词条收集构成数据基础,并基于新事物出现的随机性,用联合随机抽样的方式挖掘新的组合;最后,由专家从需求满足度及技术成本两个方面评测抽样结果组合的合理性,并举出了一个新场景挖掘的应用案例来论证方法的有效性.

Traditional architecture is an important component carrier of traditional culture. Through deep learning models, relevant entities can be automatically extracted from unstructured texts to provide data support for the protection and inheritance of traditional architecture. However, research on text information extraction oriented to this field has not been effectively carried out. In this paper, a data set of nearly 50,000 words in this field is collected, sorted out, and annotated, five types of entity labels are defined, annotation specifications are clarified, and a method of Named Entity Recognition based on pre-training model is proposed. BERT (Bidirectional Encoder Representations from Transformers) pre-training model is used to capture dynamic word vector information, Bi-directional Long Short-Term Memory (BiLSTM) module is used to capture bidirectional contextual information with positive and reverse sequences. Finally, classification mapping between labels is completed by the Conditional Random Field (CRF) module. The experiment shows that compared with other models, the BERT-BiLSTM-CRF model proposed in this experiment has a better recognition effect in this field, with F1 reaching 95.45%.

Aiming at representative buildings in Beijing, to dig out the cultural factors reflected behind the use of architectural elements in buildings, a set of cultural calculation processes for data collection, quantitative modeling, and analysis have been completed. Firstly, organize and analyze Beijing buildings' entities and relationships and the architectural elements they use and obtain related corpora. Secondly, use natural language processing methods to complete the structuring and vectorization of the corpus. Finally, combine the clustering algorithm results with the prior knowledge in the humanities field to produce conclusions. It concludes that the word vector cluster clustered by semantics can significantly represent the cultural source of the architectural elements in the corresponding category, so the application of the architectural elements to the elements can reflect the cultural connotations behind them.

Research on 6G has been carried out on a global scale.Focusing on holographic interactive services under 6G, the requirements for future network performance by studying holographic interactive scenarios and services were analyzed.A basis for business requirements for the design and research and technological evolution of 6G networks was provided.The holographic technology and application status, holographic communication and holographic interaction scenarios, as well as the technical indicators and network performance requirements of the scene business were studied.The holographic technology development stage, development maturity, holographic industry chain under 5G, and holographic technology application field distribution were defined.A holographic scene pool and scene characteristics were constructed, and six types of application scenes were formed based on the characteristics.Through the calculation of technical indicators, the bandwidth performance requirements of holographic portrait transmission were proposed.