David Ruiz

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Full Professor
F1.46




David Ruiz is Full Professor at the University of Seville. He is the leader at the Data Engineering Applications Lab at the University of Seville, focusing his research on Data Engineering, Knowledge Graphs, and Data Integration.

Research topics
Semantic Web, Web of Data, Semantic Web Services, Data Integration, Knowledge Graphs

Publications

66 entries « 1 of 11 »

2024

Sola, Fernando; Ayala, Daniel; Pulido, Marina; Ayala, Rafael; López-Cerero, Lorena; Hernández, Inma; Ruiz, David

ginmappeR: an unified approach for integrating gene and protein identifiers across biological sequence databases Journal Article

In: Bioinformatics Advances, vol. 4, no. 1, pp. vbae129, 2024, ISSN: 2635-0041.

Links | BibTeX

Bermudo, Miguel; Ayala, Daniel; Hernández, Inma; Ruiz, David; Toro, Miguel

SpaceRL-KG: Searching paths automatically combining embedding-based rewards with Reinforcement Learning in Knowledge Graphs Journal Article

In: Expert Systems With Applications, vol. 255, pp. 124410, 2024, ISSN: 0957-4174.

Links | BibTeX

2023

Ayala, Daniel; Ayala, Rafael; Vidal, Lara Sellés; Hernández, Inma; Ruiz, David

Neural Networks for Aircraft Trajectory Prediction: Answering Open Questions About Their Performance Journal Article

In: IEEE Access, vol. 11, pp. 26593-26610, 2023, ISSN: 2169-3536.

Links | BibTeX

Ayala, Rafael; Ayala, Daniel; Vidal, Lara Sellés; Ruiz, David

asteRisk - Integration and Analysis of Satellite Positional Data in R. Journal Article

In: R Journal, vol. 15, no. 1, pp. 34-54, 2023, ISSN: 2073-4859.

Links | BibTeX

Sola, Fernando; Ayala, Daniel; Ayala, Rafael; Hernández, Inma; Rivero, Carlos R; Ruiz, David

AYNEXT-tools for streamlining the evaluation of link prediction techniques Journal Article

In: SoftwareX, vol. 23, pp. 101474, 2023, ISSN: 2352-7110.

Links | BibTeX

Sola, Fernando; Ayala, Daniel; Hernández, Inma; Ruiz, David

Deep embeddings and Graph Neural Networks: using context to improve domain-independent predictions Journal Article

In: Applied Intelligence, vol. 53, no. 19, pp. 22415–22428, 2023, ISSN: 1573-7497.

Links | BibTeX

66 entries « 1 of 11 »