Horacio Saggion
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Horacio Saggion is a person.
References
- Professional Homepage: http://www.dcs.shef.ac.uk/~saggion/horaciowebpage/index.html
- DBLP Page: http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/s/Saggion:Horacio.html
- Google Scholar Author Page: http://scholar.google.com/citations?user=WMrCFCIAAAAJ
2016
- (Espinosa-Anke et al., 2016) ⇒ Luis Espinosa-Anke, Roberto Carlini, Horacio Saggion, and Francesco Ronzano. (2016). “DEFEXT: A Semi Supervised Definition Extraction Tool.” In: GLOBALEX 2016 Lexicographic Resources for Human Language Technology Workshop Programme.
2008
- (Yankova et al., 2008) ⇒ Milena Yankova, Horacio Saggion, and Hamish Cunningham. (2008). “A Framework for Identity Resolution and Merging for Multi-source Information Extraction.” In: Proceedings of LREC Conference (LREC 2008).
- (Saggion, 2008) ⇒ Horacio Saggion. (2008). “Experiments on Semantic based Clustering for Cross-Document Coreference.” In: International Joint Conference on Natural Language Processing, Hyderabad, India, January. AFNLP.
2007
- (Funk et al., 2007) ⇒ Adam Funk, Diana Maynard, Horacio Saggion, and Kalina Bontcheva. (2007). “Ontological Integration of Information Extraction from Multiple Sources.” In: Proceedings of the RANLP 2007 Workshop on Multi-source Multilingual Information Extraction and Summarization (MMIES 2007)
- (Saggion et al., 2007) ⇒ Horacio Saggion, Adam Funk, Diana Maynard, and Kalina Bontcheva. (2007). “Ontology-based Information Extraction for Business Intelligence.” In: Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC 2007)
- ABSTRACT: Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.