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1. MammoTab: a giant and comprehensive dataset for Semantic Table Interpretation

Author

Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, Palmonari, M, Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, and Palmonari, M

Abstract

In this paper, we present MammoTab, a dataset composed of 1M Wikipedia tables extracted from over 20M Wikipedia pages and annotated through Wikidata. The lack of this kind of datasets in the state- of-the-art makes MammoTab a good resource for testing and training Semantic Table Interpretation approaches. The dataset has been designed to cover several key challenges, such as disambiguation, homonymy, and NIL-mentions. The dataset has been evaluated using MTab, one of the best approaches of the SemTab challenge.

Published
2023

2. Results of the Ontology Alignment Evaluation Initiative 2022

Author

Pour, M. A. N., Algergawy, A., Buche, P., Castro, L. J., Chen, J., Dong, H., Fallatah, O., Faria, D., Fundulaki, I., Hertling, S., He, Y., Horrocks, I., Huschka, M., Ibanescu, L., Jiménez-Ruiz, E., Karam, N., Laadhar, A., Lambrix, Patrick, Li, H., Li, Y., Michel, F., Nasr, E., Paulheim, H., Pesquita, C., Saveta, T., Shvaiko, P., Trojahn, C., Verhey, C., Wu, M., Yaman, B., Zamazal, O., Zhou, L., Pour, M. A. N., Algergawy, A., Buche, P., Castro, L. J., Chen, J., Dong, H., Fallatah, O., Faria, D., Fundulaki, I., Hertling, S., He, Y., Horrocks, I., Huschka, M., Ibanescu, L., Jiménez-Ruiz, E., Karam, N., Laadhar, A., Lambrix, Patrick, Li, H., Li, Y., Michel, F., Nasr, E., Paulheim, H., Pesquita, C., Saveta, T., Shvaiko, P., Trojahn, C., Verhey, C., Wu, M., Yaman, B., Zamazal, O., and Zhou, L.

Abstract

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities. The OAEI 2022 campaign offered 14 tracks and was attended by 18 participants. This paper is an overall presentation of that campaign. © 2022 Copyright for this paper by its authors.

Published
2022

3. MammoTab: a giant and comprehensive dataset for Semantic Table Interpretation

Author

Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, Palmonari, M, Efthymiou, V, Jiménez-Ruiz, E, Chen, J, Cutrona, V, Hassanzadeh, O, Sequeda, J, Srinivas, K, Abdelmageed, N, Hulsebos, M, Marzocchi, M, Cremaschi, M, Pozzi, R, Avogadro, R, and Palmonari, M

Abstract

In this paper, we present MammoTab, a dataset composed of 1M Wikipedia tables extracted from over 20M Wikipedia pages and annotated through Wikidata. The lack of this kind of datasets in the state- of-the-art makes MammoTab a good resource for testing and training Semantic Table Interpretation approaches. The dataset has been designed to cover several key challenges, such as disambiguation, homonymy, and NIL-mentions. The dataset has been evaluated using MTab, one of the best approaches of the SemTab challenge.

Published
2022

4. Tough Tables: Carefully Evaluating Entity Linking for Tabular Data

Author

Pan J.Z.,Tamma V.,d'Amato C.,Janowicz K.,Fu B.,Polleres A.,Seneviratne O.,Kagal L., Cutrona, V, Bianchi, F, Jiménez-Ruiz, E, Palmonari, M, Pan J.Z.,Tamma V.,d'Amato C.,Janowicz K.,Fu B.,Polleres A.,Seneviratne O.,Kagal L., Cutrona, V, Bianchi, F, Jiménez-Ruiz, E, and Palmonari, M

Abstract

Table annotation is a key task to improve querying the Web and support the Knowledge Graph population from legacy sources (tables). Last year, the SemTab challenge was introduced to unify different efforts to evaluate table annotation algorithms by providing a common interface and several general-purpose datasets as a ground truth. The SemTab dataset is useful to have a general understanding of how these algorithms work, and the organizers of the challenge included some artificial noise to the data to make the annotation trickier. However, it is hard to analyze specific aspects in an automatic way. For example, the ambiguity of names at the entity-level can largely affect the quality of the annotation. In this paper, we propose a novel dataset to complement the datasets proposed by SemTab. The dataset consists of a set of high-quality manually-curated tables with non-obviously linkable cells, i.e., where values are ambiguous names, typos, and misspelled entity names not appearing in the current version of the SemTab dataset. These challenges are particularly relevant for the ingestion of structured legacy sources into existing knowledge graphs. Evaluations run on this dataset show that ambiguity is a key problem for entity linking algorithms and encourage a promising direction for future work in the field.

Published
2020

5. Results of SemTab 2020

Author

Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen, Kavitha Srinivas, Vincenzo Cutrona, Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, Cutrona, V, Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen, Kavitha Srinivas, Vincenzo Cutrona, Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, and Cutrona, V

Abstract

SemTab 2020 was the second edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 19th International Semantic Web Conference (ISWC) and the 15th Ontology Matching (OM) Workshop. SemTab provides a common framework to conduct a systematic evaluation of state-of-the-art systems.

Published
2020

6. MantisTable SE: An efficient approach for the semantic table interpretation

Author

Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, Cutrona, V, Cremaschi, M, Avogadro, R, Barazzetti, A, Chieregato, D, Cremaschi M., Avogadro R., Barazzetti A., Chieregato D., Jiménez-Ruiz, E, Hassanzadeh, O, Efthymiou, V, Chen, J, Srinivas, K, Cutrona, V, Cremaschi, M, Avogadro, R, Barazzetti, A, Chieregato, D, Cremaschi M., Avogadro R., Barazzetti A., and Chieregato D.

Abstract

In this paper, we present a novel unsupervised and automatic approach for Semantic Table Interpretation. The technique presented is performed against DBpedia and Wikidata, and it can be easily adapted to any other Knowledge Graph (KG). Moreover, we provide a tool (LamAPI) that allows to efficiently fetch data needed for Semantic Table Interpretation (STI) tasks from the KG dumps.

Published
2020

8. The Bayesian ontology reasoner is born!

Author

Dumontier, M, Glimm, B, Gonçalves, RS, Horridge, M, Jiménez-Ruiz, E, Matentzoglu, N, Parsia, B, Stamou, GB, Stoilos, G, Ceylan, I, Mendez, J, Peñaloza, R, Dumontier, M, Glimm, B, Gonçalves, RS, Horridge, M, Jiménez-Ruiz, E, Matentzoglu, N, Parsia, B, Stamou, GB, Stoilos, G, Ceylan, I, Mendez, J, and Peñaloza, R

Abstract

Bayesian ontology languages are a family of probabilistic ontology languages that allow to encode probabilistic information over the axioms of an ontology with the help of a Bayesian network. The Bayesian ontology language BEL is an extension of the lightweight Description Logic (DL) EL within the above-mentioned framework. We present the system BORN that implements the probabilistic subsumption problem for BEL.

Published
2015

9. The Bayesian ontology reasoner is born!

Author

Dumontier, M, Glimm, B, Gonçalves, RS, Horridge, M, Jiménez-Ruiz, E, Matentzoglu, N, Parsia, B, Stamou, GB, Stoilos, G, Ceylan, I, Mendez, J, Peñaloza, R, Dumontier, M, Glimm, B, Gonçalves, RS, Horridge, M, Jiménez-Ruiz, E, Matentzoglu, N, Parsia, B, Stamou, GB, Stoilos, G, Ceylan, I, Mendez, J, and Peñaloza, R

Abstract

Bayesian ontology languages are a family of probabilistic ontology languages that allow to encode probabilistic information over the axioms of an ontology with the help of a Bayesian network. The Bayesian ontology language BEL is an extension of the lightweight Description Logic (DL) EL within the above-mentioned framework. We present the system BORN that implements the probabilistic subsumption problem for BEL.

Published
2015

10. Aplicación de nuevas técnicas docentes en la asignatura Sistemas Cliente/Servidor

Author

Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., Rajadell, O., Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., and Rajadell, O.

Abstract

En este trabajo mostramos nuestras experiencias en la aplicación de metodologías de aprendizaje cooperativo y basado en proyectos en la asignatura Sistemas Cliente/Servidor en los cursos académicos 2008/2009 y 2009/2010.

Published
2011

11. Aplicación de nuevas técnicas docentes en la asignatura Sistemas Cliente/Servidor

Author

Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., Rajadell, O., Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., and Rajadell, O.

Abstract

En este trabajo mostramos nuestras experiencias en la aplicación de metodologías de aprendizaje cooperativo y basado en proyectos en la asignatura Sistemas Cliente/Servidor en los cursos académicos 2008/2009 y 2009/2010.

Published
2011

12. Aplicación de nuevas técnicas docentes en la asignatura Sistemas Cliente/Servidor

Author

Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., Rajadell, O., Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., and Rajadell, O.

Abstract

En este trabajo mostramos nuestras experiencias en la aplicación de metodologías de aprendizaje cooperativo y basado en proyectos en la asignatura Sistemas Cliente/Servidor en los cursos académicos 2008/2009 y 2009/2010.

Published
2011

13. Aplicación de nuevas técnicas docentes en la asignatura Sistemas Cliente/Servidor

Author

Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., Rajadell, O., Corchuelo Gil, Rafael, Jiménez Rodríguez, María José, Romero Ternero, María del Carmen, Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII), Universidad de Sevilla. Departamento de Tecnología Electrónica, Jiménez Ruiz, E., Llido, D., Berlanga, R., and Rajadell, O.

Abstract

En este trabajo mostramos nuestras experiencias en la aplicación de metodologías de aprendizaje cooperativo y basado en proyectos en la asignatura Sistemas Cliente/Servidor en los cursos académicos 2008/2009 y 2009/2010.

Published
2011

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