We demonstrate GraphDBLP, a tool to allow researchers for querying the DBLP bibliography as a graph. The DBLP source data were enriched with semantic similarity relationships computed using wordembeddings. A user can interact with the system either via a Web-based GUI or using a shell-interface, both provided with three parametric and pre-defined queries. GraphDBLP would represent a first graph-database instance of the computer scientist network, that can be improved through new relationships and properties on nodes at any time, and this is the main purpose of the tool, that is freely available on Github. To date, GraphDBLP contains 5+ million nodes and 24+ million relationship.

Mercorio, F., Mezzanzanica, M., Moscato, V., Picariello, A., Sperlì, G. (2020). A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases. In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) (pp.760-763). Springer [10.1007/978-3-030-46133-1_46].

A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases

Mercorio, F
;
Mezzanzanica, M;
2020

Abstract

We demonstrate GraphDBLP, a tool to allow researchers for querying the DBLP bibliography as a graph. The DBLP source data were enriched with semantic similarity relationships computed using wordembeddings. A user can interact with the system either via a Web-based GUI or using a shell-interface, both provided with three parametric and pre-defined queries. GraphDBLP would represent a first graph-database instance of the computer scientist network, that can be improved through new relationships and properties on nodes at any time, and this is the main purpose of the tool, that is freely available on Github. To date, GraphDBLP contains 5+ million nodes and 24+ million relationship.
paper
Graph Databases; Big Scholarly Data; Word Embeddings
English
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2019 16-20 September
2019
Mercorio, F; Mezzanzanica, M; Moscato, V; Picariello, A; Sperlì, G
Brefeld U.,Fromont E.,Hotho A.,Knobbe A.,Maathuis M.,Robardet C.
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)
9783030461324
2020
11908
760
763
https://link.springer.com/chapter/10.1007/978-3-030-46133-1_46
reserved
Mercorio, F., Mezzanzanica, M., Moscato, V., Picariello, A., Sperlì, G. (2020). A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases. In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) (pp.760-763). Springer [10.1007/978-3-030-46133-1_46].
File in questo prodotto:
File Dimensione Formato  
GraphDBLP_ECML_CR.pdf

Solo gestori archivio

Tipologia di allegato: Author’s Accepted Manuscript, AAM (Post-print)
Dimensione 715.92 kB
Formato Adobe PDF
715.92 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/253069
Citazioni
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 0
Social impact