Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/130471| Title: | From linguistic linked data to big data |
| Authors: | Trajanov, Dimitar Apostol, Elena-Simona Garabík, Radovan Gkirtzou, Katerina Gromann, Dagmar Liebeskind, Chaya Palma, Cosimo Rosner, Michael Sampri, Alexia Sérasset, Gilles Spahiu, Blerina Truică, Ciprian-Octavian Oleskeviciene, Giedre Valunaite |
| Keywords: | Linked data Big data Computer-aided engineering Semantic Web Data structures (Computer science) |
| Issue Date: | 2024 |
| Citation: | Trajanov, D., Apostol, E. S., Garabík, R., Gkirtzou, K., Gromann, D., Liebeskind, C., ... & Oleškevičienė, G. V. (2024, May). From Linguistic Linked Data to Big Data. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), Torino, Italy. 489–7502. |
| Abstract: | With advances in the field of Linked (Open) Data (LOD), language data on the LOD cloud has grown in number, size, and variety. With an increased volume and variety of language data, optimizations of methods for distributing, storing, and querying these data become more central. To this end, this position paper investigates use cases at the intersection of LLOD and Big Data, existing approaches to utilizing Big Data techniques within the context of linked data, and discusses the challenges and benefits of this union. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/130471 |
| Appears in Collections: | Scholarly Works - FacICTAI |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| From_linguistic_linked_data_to_big_data_2024.pdf | 294.33 kB | Adobe PDF | View/Open |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.