In this paper, we propose SemTree, a novel semantic index for supporting retrieval of information from huge amount of document collections, assuming that semantics of a document can be effectively expressed by a set of 〈subject, predicate, object〉 statements as in the RDF model. A distributed version of KD-Tree has been then adopted for providing a scalable solution to the document indexing, leveraging the mapping of triples in a vectorial space. We investigate the feasibility of our approach in a real case study, considering the problem of finding inconsistencies in documents related to software requirements and report some preliminary experimental results.
SemTree: An index for supporting semantic retrieval of documents
Persia F.;
2015-01-01
Abstract
In this paper, we propose SemTree, a novel semantic index for supporting retrieval of information from huge amount of document collections, assuming that semantics of a document can be effectively expressed by a set of 〈subject, predicate, object〉 statements as in the RDF model. A distributed version of KD-Tree has been then adopted for providing a scalable solution to the document indexing, leveraging the mapping of triples in a vectorial space. We investigate the feasibility of our approach in a real case study, considering the problem of finding inconsistencies in documents related to software requirements and report some preliminary experimental results.File | Dimensione | Formato | |
---|---|---|---|
semtree.pdf
solo utenti autorizzati
Descrizione: Articolo principale
Tipologia:
Documento in Versione Editoriale
Licenza:
Creative commons
Dimensione
702.02 kB
Formato
Adobe PDF
|
702.02 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.