http://www.cnr.it/ontology/cnr/individuo/prodotto/ID172640
Structural similarity in geographical queries to improve query answering (Contributo in atti di convegno)
- Type
- Label
- Structural similarity in geographical queries to improve query answering (Contributo in atti di convegno) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Alternative label
D'Ulizia Arianna; Ferri Fernando; Formica Anna; Grifoni Patrizia; Rafanelli Maurizio (2007)
Structural similarity in geographical queries to improve query answering
in ACM Symposium Applied Computing, Track on Advances in Spatial and Image-based Information Systems (ASIIS 07), Seoul (KR), MAR 11-15, 2007
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- D'Ulizia Arianna; Ferri Fernando; Formica Anna; Grifoni Patrizia; Rafanelli Maurizio (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- SAC '07 Proceedings of the 2007 ACM symposium on Applied computing (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- a cura di: ACM
pp. 19-23
Data evento: March 11-15 2007 (literal)
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- D'Ulizia Arianna; Ferri Fernando; Grifoni Patrizia: Institute of Research on Population and Social Policies - National Research Council
Formica Anna; Rafanelli Maurizio: Institute for Systems Analysis and Computer Science - National Research Council (literal)
- Titolo
- Structural similarity in geographical queries to improve query answering (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-1-59593-480-2 (literal)
- Abstract
- The paper proposes a method for query approximation in Geographic Information Systems. In particular, the problem of matching a query with imprecise or missing data is analyzed and an approach for the relaxation of query constraints is proposed. Query approximation is performed by relaxing structural constraints, according to an extension of a previous proposal for evaluating concept similarity in an ontology management system [1] inspired by the maximum weighted matching problem in bipartite graphs. In our approach, we start from a weighted hierarchy of geographical objects evaluated using WordNet, a lexical database for the English language available on the Internet. If a concept contained in a query has no match in the database, the query is approximated using a structural similarity graph that connects all geographical concepts by the lowest structural distance. The aim of the proposed methodology is to relax structural query constraints, in order to obtain meaningful answers for imprecise or missing data. (literal)
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