Results obtained querying language-specic DBpedia chap- ters SPARQL endpoints for the same query can be related by several het- erogenous relations, or contain an inconsistent set of information about the same topic. To overcome this issue in question answering systems over language-specic DBpedia chapters, we propose the RADAR frame- work for information reconciliation. Starting from a categorization of the possible relations among the resulting instances, such framework: (i) classies such relations, (ii) reconciles the obtained information using argumentation theory, (iii) ranks the alternative results depending on the condence of the source in case of inconsistencies, and (iv) explains the reasons underlying the proposed ranking.
Reconciling information in DBpedia through a question answering system
ISWC 2014, 13th International Semantic Web Conference, Demo Track, October 21-23, 2014, Riva del Garda, Italy
Type:
Poster / Demo
City:
Riva del Garda
Date:
2014-10-21
Department:
Data Science
Eurecom Ref:
4453
Copyright:
CEUR
See also:
PERMALINK : https://www.eurecom.fr/publication/4453