Museum cultural relics represent a special material cultural heritage, and modern interpretations of them are needed in current society. Based on the catalogue data of cultural relics published by the State Administration of Cultural Heritage, this paper analyzes the continuity and intermittentness of cultural relics in time series by using the method of continuity judgment of cultural relics, analyzes the aggregation and migration of cultural relics in space by using the method of spatial analysis, and then uses cosine similarity to explain the similarity distribution in space and time. The results show that the overall distribution of cultural relics exhibits the characteristics of class aggregation, dynasty aggregation and regional aggregation. From the perspective of a time scale, cultural relics have different “life cycles”, displaying continuity, intermittentness, and similarity. From the perspective of a spatial scale, the cultural relic distribution forms a small “cultural communication circle”, showing aggregation, migration, and similarity. The temporal and spatial distribution of cultural relics exhibited more similar characteristics among dynasties that were closer together than those that were far away.

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The cultural meme is the smallest unit constituting a dynasty′s culture, which has the same inheritance and variability as biological genes. Here, based on the name of cultural relics, we extract cultural memes through semantic word segmentation, word frequency statistics, and the synonym merging method, and construct dynasty cultural meme vectors. We analyzed color, auxiliary, texture, shape, and overall networks of five types of model to construct the culture network, using the social network analysis method, and explored the clustering and degrees of centrality characteristics of cultural memes. We then analyzed the similarities and differences among cultures of the dynasties. The main conclusions are as follows: (1) Cultural memes represent different cultural characteristics of dynasties, and the inheritance and differences among dynasties’ cultures are closely related to their historical background. (2) Prevalence memes construct the cultural label of dynasties, which can roughly restore the cultural appearance of dynasties through fewer prevalence memes. (3) The use of community detection with a cultural meme network can determine the clustering of dynasties′ cultures, and the degree of centrality further reflects the main cultural characteristics presented by successive dynasties.

The coexistence of different cultures is a distinctive feature of human society, and globalization makes the construction of cities gradually tend to be the same, so how to find the unique memes of urban culture in a multicultural environment is very important for the development of a city. Most of the previous analyses of urban style have been based on simple classification tasks to obtain the visual elements of cities, lacking in considering the most essential visual elements of cities as a whole. Therefore, based on the image data of ten representative cities around the world, we extract the visual memes via the dictionary learning method, quantify the symmetric similarities and differences between cities by using the memetic similarity, and interpret the reasons for the similarities and differences between cities by using the memetic similarity and sparse representation. The experimental results show that the visual memes have certain limitations among different cities, i.e., the elements composing the urban style are very similar, and the linear combinations of visual memes vary widely as the reason for the differences in the urban style among cities.