Supporting Springer Nature Editors by means of Semantic Technologies. - Francesco Osborne; Angelo Antonio Salatino; Aliaksandr Birukou; Thiviyan Thanapalasingam; Enrico Motta (ISWC (Posters, Demos & Industry Tracks), 2017)

Smart Book Recommender: A Semantic Recommendation Engine for Editorial Products. - Francesco Osborne; Thiviyan Thanapalasingam; Angelo Antonio Salatino; Aliaksandr Birukou; Enrico Motta (ISWC (Posters, Demos & Industry Tracks), 2017)

The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas. - Angelo Antonio Salatino; Thiviyan Thanapalasingam; Andrea Mannocci; Francesco Osborne; Enrico Motta (ISWC (2), 2018)

Classifying Research Papers with the Computer Science Ontology. - Angelo Antonio Salatino; Thiviyan Thanapalasingam; Andrea Mannocci; Francesco Osborne; Enrico Motta (ISWC (P&D/Industry/BlueSky), 2018)

Ontology-Based Recommendation of Editorial Products. - Thiviyan Thanapalasingam; Francesco Osborne; Aliaksandr Birukou; Enrico Motta (ISWC (2), 2018)

The Smart Book Recommender: An Ontology-Driven Application for Recommending Editorial Products. - Thiviyan Thanapalasingam; Francesco Osborne; Aliaksandr Birukou; Enrico Motta (ISWC (P&D/Industry/BlueSky), 2018)

The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles. - Angelo Antonio Salatino; Francesco Osborne; Thiviyan Thanapalasingam; Enrico Motta (TPDL, 2019)

Linked Open Data Validity - A Technical Report from ISWS 2018. - Tayeb Abderrahmani Ghor; Esha Agrawal; Mehwish Alam; Omar Alqawasmeh; Claudia d'Amato; Amina Annane; Amr Azzam; Andrew Berezovskyi; Russa Biswas; Mathias Bonduel; Quentin Brabant; Cristina-Iulia Bucur; et al. (CoRR, 2019)

The Computer Science Ontology: A Comprehensive Automatically-Generated Taxonomy of Research Areas. - Angelo A. Salatino; Thiviyan Thanapalasingam; Andrea Mannocci; Aliaksandr Birukou; Francesco Osborne; Enrico Motta (Data Intell., 2020)

Prompting as Probing: Using Language Models for Knowledge Base Construction. - Dimitrios Alivanistos; Selene Baez Santamaría; Michael Cochez; Jan-Christoph Kalo; Emile van Krieken; Thiviyan Thanapalasingam (LM-KBC@ISWC, 2022)

Relational graph convolutional networks: a closer look. - Thiviyan Thanapalasingam; Lucas van Berkel; Peter Bloem; Paul Groth (PeerJ Comput. Sci., 2022)

A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference. - Emile van Krieken; Thiviyan Thanapalasingam; Jakub M. Tomczak; Frank van Harmelen; Annette ten Teije (NeurIPS, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (CoRR, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks. - Taraneh Younesian; Daniel Daza; Emile van Krieken; Thiviyan Thanapalasingam; Peter Bloem (Trans. Mach. Learn. Res., 2025)