Author: Amato, A.; Amato, F.; Barolli, L.; Bonavolontà , F.
Title: Automatic Measurement of Acquisition for COVID-19 Related Information Cord-id: xjxw7s7j Document date: 2022_1_1
ID: xjxw7s7j
Snippet: This paper investigates data representation and extraction procedures for the management of domain-specific information regarding COVID-19 information. To integrate among different data sources, including data contained in COVID-19 related clinical texts written in natural language, Natural Language Processing (NLP) techniques and the main tools available for this purpose were studied. In particular, we use an NLP pipeline implemented in python to extract relevant information taken from COVID-19
Document: This paper investigates data representation and extraction procedures for the management of domain-specific information regarding COVID-19 information. To integrate among different data sources, including data contained in COVID-19 related clinical texts written in natural language, Natural Language Processing (NLP) techniques and the main tools available for this purpose were studied. In particular, we use an NLP pipeline implemented in python to extract relevant information taken from COVID-19 related literature and apply lexicometric measures on it. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Search related documents:
Co phrase search for related documents- Try single phrases listed below for: 1
Co phrase search for related documents, hyperlinks ordered by date