The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
DBpedia spotlight: shedding light on the web of documents
Open accessAbstract
Interlinking text documents with Linked Open Data enables the Web of Data to be used as background knowledge within document-oriented applications such as search and faceted browsing. As a step towards interconnecting the Web of Documents with the Web of Data, we developed DBpedia Spotlight, a system for automatically annotating text documents with DBpedia URIs. DBpedia Spotlight allows users to configure the annotations to their specific needs through the DBpedia Ontology and quality measures such as prominence, topical pertinence, contextual ambiguity and disambiguation confidence. We compare our approach with the state of the art in disambiguation, and evaluate our results in light of three baselines and six publicly available annotation systems, demonstrating the competitiveness of our system. DBpedia Spotlight is shared as open source and deployed as a Web Service freely available for public use.
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Cites
A vector space model for automatic indexing
Salton, G., Wong, A., & Yang, C. S. (1975) · Communications of the ACM · doi:10.1145/361219.361220 · Cited by 7,521
Cited by
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Why Reinvent the Wheel: Let's Build Question Answering Systems Together
Singh, K., Lange, C., Vidal, M. E., Lehmann, J., Auer, S., Radhakrishna, A. S., Both, A., Shekarpour, S., Lytra, I., Usbeck, R., et al. (2018) · Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18 · doi:10.1145/3178876.3186023 · Cited by 102
Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text
Sakor, A., Onando Mulang’, I., Singh, K., Shekarpour, S., Esther Vidal, M., Lehmann, J., & Auer, S. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1243 · Cited by 86
Data-Driven Methodology for Knowledge Graph Generation Within the Tourism Domain
Chessa, A., Fenu, G., Motta, E., Osborne, F., Reforgiato Recupero, D., Salatino, A., & Secchi, L. (2023) · IEEE Access · doi:10.1109/access.2023.3292153 · Cited by 40
Capturing Knowledge in Semantically-typed Relational Patterns to Enhance Relation Linking
Singh, K., Mulang', I. O., Lytra, I., Jaradeh, M. Y., Sakor, A., Vidal, M.-E., Lange, C., & Auer, S. (2017) · Proceedings of the Knowledge Capture Conference · doi:10.1145/3148011.3148031 · Cited by 24
Metadata
- Authors
- Mendes, P. N., Jakob, M., García-Silva, A., & Bizer, C.
- Venue
- Proceedings of the 7th International Conference on Semantic Systems
- Publisher
- ACM
- Published
- 2011-09-07
- Pages
- 1-8
- OpenAlex
- W2104583100
- Cited by
- 1,180
- References
- 1
- FWCI
- 70.35
- Type
- conference paper
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
