BI-CN/20-21-20 - Analysis of internet-based cultural transmission by knowledge graphs
Name of project: Analysis of internet-based cultural transmission by knowledge graphs
Time frame: 15.11.2020 – 14.08.2021
Coordinator: Niko Lukač
Data mining algorithms are becoming important for analysis of big data such as social networks graphs, where cultural transmission is one of the semantic components. One of the exciting new algorithms are based on knowledge graphs, which were firstly proposed by Google in 2012. Knowledge graph generally refers to an algorithm for constructing a subgraph representing semantic relation network. Currently most of the researches focus on the theoretical research of culture transmission, or on the algorithmic aspects of knowledge graph construction. Few scholars combine the two aspects, in order to study how to realize the sustainable development of culture transmission. Based on the cross media big data of culture transmission, this project fully takes the advantages of big data mining and parallel computing technology. The aim would be based on construction of knowledge graphs of culture transmission and extraction of public interest points. Relying on big data parallel computing technology, we will enhance the performance of cultural transmission analysis. The project will also have social impacts beyond the scope of the project, by disseminating the attraction of internet-based cultural transmission, while demonstrating the influence of Chinese and Slovene cultures.algorithms.