A Framework for the Paraconsistent Annotation Evidential Logic ET
Jair M. Abe, Kazumi Nakamatsu, Seiki Akama, Ari Ahrary
Journal of E - Technology, Vol. 12, No. 3, 2021.
DOI: https://doi.org/10.6025/jet/2021/12/3/76-85
Link: https://www.dline.info/jet/fulltext/v12n3/jetv12n3_2.pdf
Abstract:
Increasingly big data become a normal component of research activities. It is important to generate more formal and generic tools to deal with this process. In the current work we have described the framework of an expert system which can treat the concepts which is characterized by inconsistent and paracomplete data without the danger of trivialization. This framework has paraconsistent annotation evidential logic ET. An algorithm which is a para-analyzer is used which is the lattice of truth-values.