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Наслов: 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-мај-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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