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Conference Papers Year : 2024

From Linguistic Linked Data to Big Data

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.
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Dates and versions

hal-04541553 , version 1 (10-04-2024)

Identifiers

  • HAL Id : hal-04541553 , version 1

Cite

Dimitar Trajanov, Elena-Simona Apostol, Radovan Garabík, Katerina Gkirtzou, Dagmar Gromann, et al.. From Linguistic Linked Data to Big Data. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELDA; ICCL, May 2024, Torino, Italy. pp.7489--7502. ⟨hal-04541553⟩
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