Accommodations in Tuscany as Linked Data

Clara Bacciu, Angelica Lo Duca, Andrea Marchetti, Maurizio Tesconi


Abstract
The OpeNER Linked Dataset (OLD) contains 19.140 entries about accommodations in Tuscany (Italy). For each accommodation, it describes the type, e.g. hotel, bed and breakfast, hostel, camping etc., and other useful information, such as a short description, the Web address, its location and the features it provides. OLD is the linked data version of the open dataset provided by Fondazione Sistema Toscana, the representative system for tourism in Tuscany. In addition, to the original dataset, OLD provides also the link of each accommodation to the most common social media (Facebook, Foursquare, Google Places and Booking). OLD exploits three common ontologies of the accommodation domain: Acco, Hontology and GoodRelations. The idea is to provide a flexible dataset, which speaks more than one ontology. OLD is available as a SPARQL node and is released under the Creative Commons release. Finally, OLD is developed within the OpeNER European project, which aims at building a set of ready to use tools to recognize and disambiguate entity mentions and perform sentiment analysis and opinion detection on texts. Within the project, OLD provides a named entity repository for entity disambiguation.
Anthology ID:
L14-1036
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3542–3545
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1052_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Clara Bacciu, Angelica Lo Duca, Andrea Marchetti, and Maurizio Tesconi. 2014. Accommodations in Tuscany as Linked Data. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 3542–3545, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Accommodations in Tuscany as Linked Data (Bacciu et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1052_Paper.pdf