Enhancing open data to Linked Open Data with ODMiner

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.

Publication type: 
Contributo in atti di convegno
Author or Creator: 
Poggi, Francesco
Nuzzolese, Andrea Giovanni
Cigna, Gabriele
Publisher: 
M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen., Aachen, Germania
CEUR-WS.org, Aachen, DEU
Source: 
Fourth International Workshop on Linked Data for Information Extraction co-located with 15th International Semantic Web Conference (ISWC 2016), pp. 44–50, Kobe, Japan, 18/10/2016
Date: 
2016
Resource Identifier: 
http://www.cnr.it/prodotto/i/366576
http://www.scopus.com/record/display.url?eid=2-s2.0-84992630892&origin=inward
Language: 
Eng
ISTC Author: 
Andrea Nuzzolese's picture
Real name: