Framework of computational intelligence-enhanced knowledge base construction: Methodology and a case of gene-related cardiovascular disease
- Publisher:
- ATLANTIS PRESS
- Publication Type:
- Journal Article
- Citation:
- International Journal of Computational Intelligence Systems, 2020, 13, (1), pp. 1109-1119
- Issue Date:
- 2020-01-01
Recently Added
Filename | Description | Size | |||
---|---|---|---|---|---|
Framework of Computational Intelligence-Enhanced Knowledge Base Construction.pdf | Published version | 7.98 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Open Access
This item is new to OPUS and is not currently available.
Knowledge base construction (KBC) aims to populate knowledge bases with high-quality information from unstructured data but how to effectively conduct KBC from scientific documents with limited preknowledge is still elusive. This paper proposes a KBC framework by applying computational intelligent techniques through the integration of intelligent bibliometrics—e.g., co-occurrence analysis is used for profiling research topics/domains and identifying key players, and recommending potential collaborators based on the incorporation of a link prediction approach; an approach of scientific evolutionary pathways is exploited to trace the evolution of research topics; and a search engine incorporating with fuzzy logics, word embedding, and genetic algorithm is developed for knowledge searching and ranking. Aiming to examine and demonstrate the reliability of the proposed framework, a case of gene-related cardiovascular diseases is selected, and a knowledge base is constructed, with the validation of domain experts.
Please use this identifier to cite or link to this item: