Preprint Open Access
Massri, M.Besher;
Spahiu, Blerina;
Grobelnik, Marko;
Alexiev, Vladimir;
Palmonari, Matteo;
Roman, Dumitru
Researchers seeking to comprehend the state-of-the-art innovations in a particular field of study must examine recent patents and scientific articles in that domain. Innovation ecosystems consist of interconnected information about entities such as researchers, institutions, projects, products, and technologies. However, representing such information in a machine-readable format is challenging because concepts like "knowledge" are not easily represented. Nonetheless, even a partial representation of innovation ecosystems provides valuable insights. Therefore, representing innovation ecosystems as knowledge graphs (KGs) would enable advanced data analysis and generate new insights. To this end, we propose InnoGraph, a framework that integrates multiple heterogeneous data sources to build a Knowledge Graph of the worldwide AI innovation ecosystem.
Name | Size | |
---|---|---|
Towards InnoGraph A Knowledge Graph for AI Innovation.pdf
md5:93af4c2cc93a8b5022fd8e56f1512dbe |
589.0 kB | Download |
Towards InnoGraph A Knowledge Graph for AI Innovation.pptx
md5:2d2505722af59d1fcbf7fda2aa89477d |
677.7 kB | Download |
Views | 248 |
Downloads | 106 |
Data volume | 62.8 MB |
Unique views | 180 |
Unique downloads | 93 |