Autors: Man Tianxing., Nataly Zhukova., Tsochev, G. R.
Title: A Multilevel Intelligent Assistant for Multilevel Social Network Analysis
Keywords: social network , multilayer structure , ontology , data proc

Abstract: In recent years, social network data analysis is an emerging field. Multilevel social network analysis could help researchers to figure out comprehensive influencing factors. But the raw data extracted from life is complicated and inoperable so that the entire analysis process is multi-step and changeable. The characteristics of social network datasets at different levels are diverse. There is no general data analysis algorithms for each level. The characteristics of the data and the requirements of the task are important basis for choosing suitable analysis methods. But it is hard for non-expert researchers. This paper proposes an intelligent multilevel assistant for multilevel social network analysis and implements it based on ontology technology. Algorithms at different levels process the corresponding data forms until the appropriate output model is generated. The use of ontology technology makes this framework extensible and understandable. Such a framework is significant for non

References

    Issue

    2020 IEEE 10th International Conference on Intelligent Systems (IS), 2020, Bulgaria, DOI 10.1109/IS48319.2020.9199840

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science