Personal information

Other IDs

Scopus Author ID: 57204530984
ResearcherID: X-1748-2018

Biography

Daniel Ayala started his research trajectory during his degree studies, as an intern alumn collaborating with "The Distributed Group" thanks to an initiation to research grant and a department collaboration grant, as well as research contracts associated to research projects. Siunce then his research started to orient towards the field of structured information.

His PhD, finished in 2020, revolves around the processing and integration of structured data. His research about semantic labelling resulted in four publications as first author in JCR-indexed journals (2 Q1, 2 Q3), and two participations in GGS-indexed international conferences (ratings A and A++), one of them obtaining the prize to the best paper in the resources track.

During this PhD, he stayed for three months in the University of Leipzig, collaborating with the group led by Erhard Rahm with the goal of developping tools for the detection of matching properties in knowledge graphs.

Currently, he is part of the Data Engineering Applications Lab (DEAL), where he carries out research about topics related to the application of data engineering to knowledge graphs, with an emphasis on the application of deep learning techniques.

Activities

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Employment (2)

Universidad de Sevilla: Sevilla, Andalucía, ES

2020-10-23 to present | Profesor Sustituto Interino (Lenguajes y Sistemas Informáticos)
Employment
Source: Self-asserted source
Daniel Ayala

Universidad de Sevilla: Sevilla, Andalucía, ES

2015-09-01 to 2020-10-07 | Investigador pre-doctoral (Lenguajes y Sistemas Informáticos)
Employment
Source: Self-asserted source
Daniel Ayala

Works (9)

LEAPME: Learning-based Property Matching with Embeddings

Data & Knowledge Engineering
2022-01 | Journal article
DOI: 10.1016/j.datak.2021.101943
Part of ISSN: 0169-023X
Source: Self-asserted source
Daniel Ayala

CAFE: Knowledge graph completion using neighborhood-aware features

Engineering Applications of Artificial Intelligence
2021-08 | Journal article
DOI: 10.1016/j.engappai.2021.104302
Part of ISSN: 0952-1976
Source: Self-asserted source
Daniel Ayala

Towards the smart use of embedding and instance features for property matching

2021 IEEE 37th International Conference on Data Engineering (ICDE)
2021-04 | Conference paper
DOI: 10.1109/icde51399.2021.00209
Source: Self-asserted source
Daniel Ayala

A neural network for semantic labelling of structured information

Expert Systems with Applications
2020-04 | Journal article
DOI: 10.1016/j.eswa.2019.113053
Part of ISSN: 0957-4174
Source: Self-asserted source
Daniel Ayala

AYNEC: All You Need for Evaluating Completion Techniques in Knowledge Graphs

The Semantic Web
2019 | Book chapter
DOI: 10.1007/978-3-030-21348-0_26
Part of ISBN: 9783030213473
Part of ISBN: 9783030213480
Part of ISSN: 0302-9743
Part of ISSN: 1611-3349
Source: Self-asserted source
Daniel Ayala

Generating Rules to Filter Candidate Triples for their Correctness Checking by Knowledge Graph Completion Techniques

Proceedings of the 10th International Conference on Knowledge Capture
2019-09-23 | Conference paper
DOI: 10.1145/3360901.3364418
Source: Self-asserted source
Daniel Ayala

TAPON-MT: A versatile framework for semantic labelling

Information Systems
2019-07 | Journal article
DOI: 10.1016/j.is.2018.12.006
Part of ISSN: 0306-4379
Source: Self-asserted source
Daniel Ayala

TAPON: A two-phase machine learning approach for semantic labelling

Knowledge-Based Systems
2018 | Journal article
DOI: 10.1016/j.knosys.2018.10.017
EID:

2-s2.0-85055987288
Contributors: Ayala, D.; Hernández, I.; Ruiz, D.; Toro, M.
Source: Self-asserted source
Daniel Ayala via Scopus - Elsevier

On verifying information extractors

Advances in Intelligent Systems and Computing
2016 | Book
DOI: 10.1007/978-3-319-40159-1_34
EID:

2-s2.0-84976388551
Contributors: Hernández, D.A.
Source: Self-asserted source
Daniel Ayala via Scopus - Elsevier

Peer review (3 reviews for 2 publications/grants)

Review activity for Engineering applications of artificial intelligence. (1)
Review activity for Expert systems with applications. (2)
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