Painting Influence Evaluation Network Based on Time Series

Paintings fill people's lives. In order to explore the influence of painters on each other, major changes in the development of painting, and changes in the painting with social change, we analyze the compositions to reduce the dimension of the data. Based on the correlation of data, we establish a measurement model of painting similarity. Distances between vectors representing painters/paintings are applied to measure their similarity and use support vector machines to build classification models. We explore the evolution of painting by building a time series model for experiments. Finally, we analyze the cultural influence of paintings and identified the influence of social, political, or technological changes in the network in combination with time-series models.