MSciP 2020 : Mining Scientific Papers Volume II: Knowledge Discovery and Data Exploitation

This research topic aims at promoting interdisciplinary research in computational linguistics and natural language processing (NLP) in the field of bibliometric/scientometrics and information retrieval. It is a follow-up of the Research Topic Mining Scientific Papers: NLP-enhanced Bibliometrics.

This Research Topic aims to discuss novel approaches that focus on the processing and exploitation of data extracted from scientific literature. In particular, the possibility to enrich metadata by the full-text processing of papers offers new fields of investigation that are related to the representation of data and the production of knowledge by the aggregation of data from multiple documents. Given the wide range of available techniques, several questions arise in this field: What volume of scientific data should be considered exploitable and allow the production of new knowledge through aggregation? How can knowledge generated from data in scientific articles be represented? What types of data and knowledge can be automatically extracted from scientific articles and how can it be exploited efficiently?