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OntoClue

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Started in 2021-01-01

Description

OntoClue aims to provide a framework to optimize and compare document-similarity and doc2doc-relevance approaches based on word-embeddings and document-embeddings. Using the RELISH dataset, each approach creates document-embeddings and calculates the Cosine Similarity. An optimizer finds the best hyperparameter combination that naturally (i.e., with no further tuning or training) resembles better the three document relevance assessments cominf from RELISH. The approaches are compared using Precision (P@N) and Normalized Discounted Cumulative Gain (NDCG@N). TREC 2005 Genomics Track data has also been analyzed using a repurposed version that transforms document-to-topic relevance into document-to-document relevance. The main focus of this project relies on RELISH.

Keywords

word-embeddings, document-embeddings, ontology-embeddings, document similarity, document relevance, doc2doc relevance, ontology enrichment

Url

• URL: https://zbmed-semtec.github.io/projects/2021_OntoClue

Current project members

• Muskaan Chopra Visit Person

• Lukas Geist Visit Person

• Endri Gupta Visit Person

• Soudeh Jahanshahi Visit Person

• Nelson Quiñones Visit Person

• Rohitha Ravinder Visit Person

• Suhasini Venkatesh Visit Person

• Dietrich Rebholz-Schuhmann Visit Person

• Leyla Jael Castro Visit Person

Previous project members

• Dadi Vishnu Vardhan Visit Person

• Tim Fellerhoff Visit Person

• Georgi Lazarov Visit Person

• Sarker Sunzid Mahmud Visit Person

• Ashley Ritchie Visit Person

• Muhammad Talha Visit Person

• Guilermo Rocamora Perez Visit Person

• Benjamin Wolff Visit Person

Department

Semantic Technologies team at ZB MED

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• URL: https://zbmed-semtec.github.io/

Parent organization, consortium or research project

Deutsche Zentralbibliothek für Medizin (ZB MED) - Informationszentrum Lebenswissenschaften

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• Alternatename: ZB MED Information Centre for Life Sciences
• URL: https://zbmed.de/

NFDI4DataScience

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• URL: https://www.nfdi4datascience.de/

STELLA Living Labs Project

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• URL: https://stella-project.org

Funding

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• Identifier: 460234259

• Description: Project no. 460234259 (corresponding to the NFDI4DataScience consortium) Visit Grant

• Identifier: 407518790

• Description: Project no. 407518790 (corresponding to the STELLA project)

Outcomes

A Comparison of Vector-based Approaches for Document Similarity Using the RELISH Corpus

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• Identifier: CEUR:Vol-3466/paper5
• Cite as: Ravinder R, Fellerhof T, Dadi V, Geist L, Talha M, Rebholz-Schuhmann D, et al. A Comparison of Vector-based Approaches for Document Similarity Using the RELISH Corpus. Proceedings of the 6th Workshop on Semantic Web Solutions for Large-Scale Biomedical Data Analytics co-located with ESWC 2023. CEUR; 2023. Available: https://ceur-ws.org/Vol-3466/paper5.pdf
• Datepublished: 2023-03-01
• License: http://spdx.org/licenses/CC-BY-4.0

• URL: https://ceur-ws.org/Vol-3466/paper5.pdf#

• Authors: https://orcid.org/0009-0004-4484-6283. https://orcid.org/0000-0002-8725-1317. https://orcid.org/0000-0002-3082-7522. https://orcid.org/0000-0002-2910-7982. https://orcid.org/0000-0002-4795-3648. https://zbmed-semtec.github.io/previous_members/#muhammad-talha. https://orcid.org/0000-0002-1018-0370. https://orcid.org/0000-0003-3986-0510.

OntoClue, a framework to compare vector-based approaches for document relatedness using the RELISH corpus

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• Identifier: DOI:10.4126/FRL01-006440397s
• Cite as: Ravinder R, Fellerhoff T, Dadi VV, Geist L, Rocamora G, Talha M, et al. OntoClue, a framework to compare vector-based approaches for document relatedness using the RELISH corpus - Poster. ZB MED - Informationszentrum Lebenswissenschaften; 2023. Available: https://repository.publisso.de/resource/frl:6440397
• Datepublished: 2023-06-22
• License: http://spdx.org/licenses/CC-BY-4.0

• URL: https://repository.publisso.de/resource/frl:6440397

• Authors: https://orcid.org/0009-0004-4484-6283. https://orcid.org/0000-0002-8725-1317. https://orcid.org/0000-0002-3082-7522. https://orcid.org/0000-0002-2910-7982. https://orcid.org/0000-0002-4795-3648. https://zbmed-semtec.github.io/previous_members/#muhammad-talha. https://orcid.org/0000-0002-1018-0370. https://orcid.org/0000-0003-3986-0510.

OntoClue, a framework to compare vector-based approaches for document relatedness using the RELISH corpus - Poster

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• Identifier: CEUR:Vol-3415/paper-38
• Cite as: Ravinder R, Fellerhoff T, Dadi V, Geist L, Rocamora G, Talha M, et al. OntoClue, a framework to compare vector-based approaches for document relatedness using the RELISH corpus. CEUR; 2023. Available: https://ceur-ws.org/Vol-3415/paper-38.pdf
• Datepublished: 2023-03-01
• License: http://spdx.org/licenses/CC-BY-4.0

• URL: https://ceur-ws.org/Vol-3415/paper-38.pdf#

• Authors: https://orcid.org/0009-0004-4484-6283. https://orcid.org/0000-0002-8725-1317. https://orcid.org/0000-0002-3082-7522. https://orcid.org/0000-0002-2910-7982. https://orcid.org/0000-0002-4795-3648. https://zbmed-semtec.github.io/previous_members/#muhammad-talha. https://orcid.org/0000-0002-1018-0370. https://orcid.org/0000-0003-3986-0510.

Ontology Clustering with OWL2Vec*

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• Identifier: CEUR:Vol-2918/short3
• Cite as: Ritchie A, Chen J, Castro LJ, Rebholz-Schuhmann D, Jimenez-Ruiz E. Ontology Clustering with OWL2Vec*. CEUR Workshop Proceedings. Online: CEUR Workshop Proceedings; 2021. Available: http://ceur-ws.org/
• Datepublished: 2021-07-28
• License: http://spdx.org/licenses/CC-BY-4.0

• URL: https://ceur-ws.org/Vol-2918/short3.pdf#

• Authors: https://zbmed-semtec.github.io/previous_members/#ashley-ritchie. https://chenjiaoyan.github.io/. https://orcid.org/0000-0003-3986-0510. https://orcid.org/0000-0002-1018-0370. https://orcid.org/0000-0002-9083-4599.

Complete Medline abstracts corpus between 2015-2019 annotated Whatizit text annotation tool

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• Identifier: DOI:10.5281/zenodo.5035290
• Cite as: Lazarov G, Wolff B, Castro LJ, Rebholz-Schuhmann D. Complete Medline abstracts corpus between 2015-2019 annotated Whatizit text annotation tool. Zenodo; 2021. doi:10.5281/zenodo.5035290
• Description: Gene Ontology annotations for Medline abstracts from 2015 to 2019 using Whatizit
• Keywords: Whatizit, Semantic annotation, Medline, text-mining
• License: http://spdx.org/licenses/CC-BY-4.0

• URL: https://zenodo.org/record/5035290

• Datepublished: 2021-06-27

• Authors: https://orcid.org/0000-0002-0762-4305. https://orcid.org/0000-0001-9345-8958. https://orcid.org/0000-0003-3986-0510. https://orcid.org/0000-0002-1018-0370.

Whatizit performance evaluation against CRAFT corpus

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• Identifier: DOI:10.5281/zenodo.4903981
• Cite as: Lazarov G, Castro LJ, Rebholz-Schuhmann D. Whatizit performance evaluation against CRAFT corpus. Zenodo; 2021. doi:10.5281/zenodo.4903981
• Description: Whatizit performance evaluation against CRAFT corpus wrt Gene Ontology annotations
• Keywords: Whatizit, Semantic annotation, CRAFT, manual annotation, performance
• License: http://spdx.org/licenses/CC-BY-4.0

• URL: https://zenodo.org/record/4903981

• Datepublished: 2021-06-05

• Authors: https://orcid.org/0000-0002-0762-4305. https://orcid.org/0000-0003-3986-0510. https://orcid.org/0000-0002-1018-0370.

External contributors

• Ernesto Jimenez-Ruiz Visit Person