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.
| Original language | English |
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| Title of host publication | 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings |
| Editors | Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue |
| Place of Publication | Torino |
| Publisher | European Language Resources Association (ELRA) |
| Pages | 7489-7502 |
| Number of pages | 14 |
| ISBN (Electronic) | 9782493814104 |
| Publication status | Published - 2024 |
| Event | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 - Hybrid, Torino, Italy Duration: 20 May 2024 → 25 May 2024 |
Conference
| Conference | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 |
|---|---|
| Country/Territory | Italy |
| City | Hybrid, Torino |
| Period | 20/05/24 → 25/05/24 |
Austrian Fields of Science 2012
- 102028 Knowledge engineering
- 602011 Computational linguistics
- 602049 Terminology science
Keywords
- Big Data
- efficient processing
- Linguistic Data Science
- Linguistic Linked Open Data (LLOD)