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Parallel and Distributed Architecture for Multilingual Open Source Intelligence Systems
Date
2024-01-01
Author
Karamanlıoğlu, Alper
Yurtalan, Gokhan
Karatas, Yahya Bahadir
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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The proliferation of publicly available information across multiple languages presents both unique challenges and opportunities for Open Source Intelligence (OSINT) systems. This paper proposes a novel architecture for multilingual OSINT that is both parallel and distributed. The architecture integrates language identification and translation capabilities, enabling it to handle linguistically diverse data by transforming it into a unified format for efficient analysis. Designed specifically to address the challenges of parallel and distributed processing in OSINT systems, this architecture aims to offer scalability and performance benefits when dealing with massive data volumes. Our primary focus has been on devising strategies and tactics that address these concerns, providing a robust solution for the collection, processing and analysis of data in various languages. This work marks a significant step towards the development of more globally inclusive OSINT systems.
Subject Keywords
data scraping
,
distributed systems
,
multilingual data processing
,
open source intelligence
,
OSINT architecture
,
parallel architecture
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85200984823&origin=inward
https://hdl.handle.net/11511/110748
DOI
https://doi.org/10.1007/978-3-031-66326-0_27
Conference Name
Proceedings of the 17th European Conference on Software Architecture, ECSA 2023
Collections
Department of Computer Engineering, Conference / Seminar
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BibTeX
A. Karamanlıoğlu, G. Yurtalan, and Y. B. Karatas, “Parallel and Distributed Architecture for Multilingual Open Source Intelligence Systems,” İstanbul, Türkiye, 2024, vol. 14590 LNCS, Accessed: 00, 2024. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85200984823&origin=inward.