Abstract
This paper proposes a graph-based algorithm baptized REDEN for the disambiguation of authors’ names in French literary criticism texts and scientific essays from the 19th century. It leverages knowledge from different Linked Data sources in order to select candidates for each author mention, then performs fusion of DBpedia and BnF individuals into a single graph, and finally decides the best referent using the notion of graph centrality. Some experiments are conducted in order to identify the best size of disambiguation context and to assess the influence on centrality of specific relations represented as edges. This work will help scholars to trace the impact of authors’ ideas across different works and time periods.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Auer, S., Bryl, V., Tramp, S.: Linked Open Data - Creating Knowledge Out of Interlinked Data. In: Auer, S., Bryl, V., Tramp, S. (eds.) Linked Open Data. LNCS, vol. 8661, pp. 1–17. Springer, Heudelberg (2014)
Baget, J.F., Chein, M., Croitoru, M., Fortin, J., Genest, D., Gutierrez, A., Leclère, M., Mugnier, M.L., Salvat, E.: RDF to Conceptual Graphs Translations. In: 3rd Conceptual Structures Tool Interoperability Workshop: 17h International Conference on Conceptual Structures. LNAI, vol. 5662, p. 17. Springer, Moscow, Russia (2009)
Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Semantic Web Inf. Syst. 5(3), 1–22 (2009)
Freeman, L.C.: A set of measures of centrality based on betweenness. Sociometry, 35–41 (1977)
Frontini, F., Brando, C., Ganascia, J.G.: Domain-adapted named-entity linker using linked data. In: Proceedings of the 20th International Conference on Applications of Natural Language to Information Systems in Conjunction with the 1st Workshop on Natural Language Applications: Completing the Puzzle (accepted, 2015)
Frontini, F., Brando, C., Ganascia, J.G.: Semantic web based named entity linking for digital humanities and heritage texts. In: Proceedings of the First International Workshop Semantic Web for Scientific Heritage at the 12th ESWC 2015 Conference, pp. 77–88 (2015). http://ceur-ws.org/Vol-1364/
Hachey, B., Radford, W., Curran, J.R.: Graph-Based Named Entity Linking with Wikipedia. In: Bouguettaya, A., Hauswirth, M., Liu, L. (eds.) WISE 2011. LNCS, vol. 6997, pp. 213–226. Springer, Heidelberg (2011)
Laudy, C., Ganascia, J.G.: Information fusion using conceptual graphs: a tv programs case study. In: ICCS, pp. 158–165 (2008)
Rao, D., McNamee, P., Dredze, M.: Entity linking: Finding extracted entities in a knowledge base. In: Multi-source, Multilingual Information Extraction and Summarization, pp. 93–115. Springer (2013)
Rochat, Y.: Character Networks and Centrality. Ph.D. thesis, University of Lausanne (2014)
Sinha, R.S., Mihalcea, R.: Unsupervised graph-basedword sense disambiguation using measures of word semantic similarity. ICSC 7, 363–369 (2007)
Van Hooland, S., De Wilde, M., Verborgh, R., Steiner, T., Van de Walle, R.: Exploring entity recognition and disambiguation for cultural heritage collections. Literary and Linguistic Computing (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Brando, C., Frontini, F., Ganascia, JG. (2015). Disambiguation of Named Entities in Cultural Heritage Texts Using Linked Data Sets. In: Morzy, T., Valduriez, P., Bellatreche, L. (eds) New Trends in Databases and Information Systems. ADBIS 2015. Communications in Computer and Information Science, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-319-23201-0_51
Download citation
DOI: https://doi.org/10.1007/978-3-319-23201-0_51
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23200-3
Online ISBN: 978-3-319-23201-0
eBook Packages: Computer ScienceComputer Science (R0)