A Framework for Identity Resolution and Merging for Multi-source Information Extraction

Milena Yankova, Horacio Saggion, Hamish Cunningham


Abstract
In the context of ontology-based information extraction, identity resolution is the process of deciding whether an instance extracted from text refers to a known entity in the target domain (e.g. the ontology). We present an ontology-based framework for identity resolution which can be customized to different application domains and extraction tasks. Rules for identify resolution, which compute similarities between target and source entities based on class information and instance properties and values, can be defined for each class in the ontology. We present a case study of the application of the framework to the problem of multi-source job vacancy extraction
Anthology ID:
L08-1296
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/347_paper.pdf
DOI:
Bibkey:
Cite (ACL):
Milena Yankova, Horacio Saggion, and Hamish Cunningham. 2008. A Framework for Identity Resolution and Merging for Multi-source Information Extraction. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
A Framework for Identity Resolution and Merging for Multi-source Information Extraction (Yankova et al., LREC 2008)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/347_paper.pdf