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http://hdl.handle.net/20.500.12188/33978| 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 Serasset, Gilles Spahiu, Blerina Truica, Ciprian-Octavian Valūnaitė Oleškevičienė, Giedrė |
Keywords: | Linguistic Linked Open Data (LLOD), Big Data, Linguistic Data Science, efficient processing | Issue Date: | 22-May-2024 | Conference: | Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) | 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: | http://hdl.handle.net/20.500.12188/33978 |
| Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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| File | Size | Format | |
|---|---|---|---|
| 1743_Paper.pdf | 429.18 kB | Adobe PDF | View/Open |
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