The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Autonomously semantifying wikipedia
Abstract
Berners-Lee's compelling vision of a Semantic Web is hindered by a chicken-and-egg problem, which can be best solved by a bootstrapping method - creating enough structured data to motivate the development of applications. This paper argues that autonomously "Semantifying Wikipedia" is the best way to solve the problem. We choose Wikipedia as an initial data source, because it is comprehensive, not too large, high-quality, and contains enough manually-derived structure to bootstrap an autonomous, self-supervised process. We identify several types of structures which can be automatically enhanced in Wikipedia (e.g., link structure, taxonomic data, infoboxes, etc.), and we describea prototype implementation of a self-supervised, machine learning system which realizes our vision. Preliminary experiments demonstrate the high precision of our system's extracted data - in one case equaling that of humans.
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Cites
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Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
Lafferty, J., McCallum, A., & Pereira, F. C. N. (2001) · ScholarlyCommons (University of Pennsylvania) · Cited by 12,935
Berners-Lee, T., Hendler, J., & Lassila, O. (2001) · Scientific American · doi:10.1038/scientificamerican0501-34 · Cited by 8,651
Popular Ensemble Methods: An Empirical Study
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Yago: a core of semantic knowledge
Suchanek, F. M., Kasneci, G., & Weikum, G. (2007) · Proceedings of the 16th international conference on World Wide Web · doi:10.1145/1242572.1242667 · Cited by 2,512
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
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Open information extraction from the web
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Unsupervised named-entity extraction from the Web: An experimental study
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Self-citationUsing Maximum Entropy for Text Classification
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Cited by
DBpedia – A large-scale, multilingual knowledge base extracted from Wikipedia
Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P. N., Hellmann, S., Morsey, M., van Kleef, P., Auer, S., et al. (2015) · Semantic Web · doi:10.3233/sw-140134 · Cited by 3,168
Distant supervision for relation extraction without labeled data
Mintz, M., Bills, S., Snow, R., & Jurafsky, D. (2009) · Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - ACL-IJCNLP '09 · doi:10.3115/1690219.1690287 · Cited by 2,752
YAGO: A Large Ontology from Wikipedia and WordNet
Suchanek, F. M., Kasneci, G., & Weikum, G. (2008) · Journal of Web Semantics · doi:10.1016/j.websem.2008.06.001 · Cited by 904
TAGME: on-the-fly annotation of short text fragments (by wikipedia entities)
Ferragina, P., & Scaiella, U. (2010) · Proceedings of the 19th ACM international conference on Information and knowledge management · doi:10.1145/1871437.1871689 · Cited by 743
Leveraging Linguistic Structure For Open Domain Information Extraction
Angeli, G., Johnson Premkumar, M. J., & Manning, C. D. (2015) · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · doi:10.3115/v1/p15-1034 · Cited by 725
Metadata
- Authors
- Wu, F., & Weld, D. S.
- Venue
- Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
- Publisher
- ACM
- Published
- 2007-11-06
- Pages
- 41-50
- OpenAlex
- W2146304342
- Cited by
- 375
- References
- 25
- FWCI
- 20.82
- Type
- conference paper
- Language
- en
- Open access
- closed
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