A knowledge graph embeddings based approach for author name disambiguation using literals.

Autor/inn/en	Santini, Cristian; Gesese, Genet Asefa; Peroni, Silvio; Gangemi, Aldo; Sack, Harald; Alam, Mehwish
Titel	A knowledge graph embeddings based approach for author name disambiguation using literals.
Quelle	In: Scientometrics, (2022) 8, S.4887-4912 PDF als Volltext Verfügbarkeit
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0138-9130
DOI	10.1007/s11192-022-04426-2
Schlagwörter	Author Name Disambiguation; Bibliographic data; Citation data; Clustering; Knowledge graph embeddings; Open citations
Abstract	Abstract Scholarly data is growing continuously containing information about the articles from a plethora of venues including conferences, journals, etc. Many initiatives have been taken to make scholarly data available in the form of Knowledge Graphs (KGs). These efforts to standardize these data and make them accessible have also led to many challenges such as exploration of scholarly articles, ambiguous authors, etc. This study more specifically targets the problem of Author Name Disambiguation (AND) on Scholarly KGs and presents a novel framework, Literally Author Name Disambiguation (LAND), which utilizes Knowledge Graph Embeddings (KGEs) using multimodal literal information generated from these KGs. This framework is based on three components: (1) multimodal KGEs, (2) a blocking procedure, and finally, (3) hierarchical Agglomerative Clustering. Extensive experiments have been conducted on two newly created KGs: (i) KG containing information from Scientometrics Journal from 1978 onwards (OC-782K), and (ii) a KG extracted from a well-known benchmark for AND provided by AMiner (AMiner-534K). The results show that our proposed architecture outperforms our baselines of 8–14% in terms of $ F_{1} $ score and shows competitive performances on a challenging benchmark such as AMiner. The code and the datasets are publicly available through Github (https://github.com/sntcristian/and-kge) and Zenodo (https://doi.org/10.5281/zenodo.6309855) respectively.
Erfasst von	OLC
Update	2023/2/05