Mining Scholarly Publications for Scientific Knowledge Graph Construction

Davide Buscaldi;Danilo Dessì;Diego Reforgiato Recupero
2019-01-01

Abstract

In this paper, we present a preliminary approach that uses a set of NLP and Deep Learning methods for extracting entities and relationships from research publications and then integrates them in a Knowledge Graph. More specifically, we (i) tackle the challenge of knowledge extraction by employing several state-of-the-art Natural Language Processing and Text Mining tools, (ii) describe an approach for integrating entities and relationships generated by these tools, and (iii) analyse an automatically generated Knowledge Graph including 10, 425 entities and 25, 655 relationships in the field of Semantic Web.
2019
Inglese
The Semantic Web: ESWC 2019 Satellite Events
11762
8
12
5
16th Extended Semantic Web Conference, ESWC 2019
Esperti anonimi
June 2-6, 2019
Portoroz, Slovenia
scientifica
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Buscaldi, Davide; Dessi', Danilo; Motta, Enrico; Osborne, Francesco; REFORGIATO RECUPERO, DIEGO ANGELO GAETANO
273
5
4.1 Contributo in Atti di convegno
reserved
info:eu-repo/semantics/conferencePaper
Files in This Item:
File Size Format  
ESWC2019-Poster.pdf

Solo gestori archivio

Type: versione post-print
Size 164.09 kB
Format Adobe PDF
164.09 kB Adobe PDF & nbsp; View / Open   Request a copy

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Questionnaire and social

Share on:
Impostazioni cookie