In this paper, we propose a framework allowing researchers to optimize their academic evaluation. More specifically, we design a specific module for skill management and integrate it with other components of a framework managing a University knowledge base; the main goals of this module are to allow researchers to easily link competences to their papers, to automatically extract the competences acquired by means of a new paper added to the knowledge base, and to automatically detect missing publications and citations in Scopus, and signal them to Elsevier.
D'Auria, D., Persia, F. (2018). Design of a framework allowing researchers to optimize their academic evaluation. In Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence for Industries, AI4I 2018 (pp.89-91). IEEE [10.1109/AI4I.2018.8665687].
Design of a framework allowing researchers to optimize their academic evaluation
D'Auria, D;
2018
Abstract
In this paper, we propose a framework allowing researchers to optimize their academic evaluation. More specifically, we design a specific module for skill management and integrate it with other components of a framework managing a University knowledge base; the main goals of this module are to allow researchers to easily link competences to their papers, to automatically extract the competences acquired by means of a new paper added to the knowledge base, and to automatically detect missing publications and citations in Scopus, and signal them to Elsevier.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
