Data di Pubblicazione:
2016
Citazione:
Enhancing open data to Linked Open Data with ODMiner / Poggi, F.; Nuzzolese, A. G.; Cigna, G.. - 1699:(2016), pp. 44-50. ( 4th International Workshop on Linked Data for Information Extraction, LD4IE 2016 jpn 2016).
Abstract:
In this paper we introduce ODMiner, an automatic tool that enhances open datasets provided in heterogenous structured formats (e.g. JSON, CSV, XML, etc.) to Linked Open Data. ODMiner mines OD by recognising well known data types and formats (e.g., dates, emails, currencies, etc.) and by exploiting well known open linked datasets and vocabularies (e.g. DBpedia, WordNet, etc.) in order to extract named entities and relations between the open dataset elements. ODMiner is designed as modular and extensible software architecture and its process can be customised in order to address specific needs of final data representation and modelling. Finally, an evaluation of ODMiner with heterogenous multi-language OD datasets is provided in order to give evidence of its practical effectiveness.
Tipologia CRIS:
Relazione in Atti di Convegno
Elenco autori:
Poggi, F.; Nuzzolese, A. G.; Cigna, G.
Link alla scheda completa:
Titolo del libro:
CEUR Workshop Proceedings
Pubblicato in: