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A Search Engine for Scientific Publications: a Cybersecurity Case Study

arXiv 2107.00082 ↗First posted 30 Jun 2021cs.AI cs.IRcited by 0

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Abstract (arXiv)

Cybersecurity is a very challenging topic of research nowadays, as digitalization increases the interaction of people, software and services on the Internet by means of technology devices and networks connected to it. The field is broad and has a lot of unexplored ground under numerous disciplines such as management, psychology, and data science. Its large disciplinary spectrum and many significant research topics generate a considerable amount of information, making it hard for us to find what we are looking for when researching a particular subject. This work proposes a new search engine for scientific publications which combines both information retrieval and reading comprehension algorithms to extract answers from a collection of domain-specific documents. The proposed solution although being applied to the context of cybersecurity exhibited great generalization capabilities and can be easily adapted to perform under other distinct knowledge domains.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 28 references that are in the map. First posted on arXiv 30 Jun 2021.

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References · 13

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  11. 2019Ten AI Stepping Stones for Cybersecuritycited by 2
  12. 2019Using Camouflaged Cyber Simulations as a Model to Ensure Validity in Cybersecurity Experimentationcited by 1
1 more
  1. 2021Robust Attack Detection Approach for IIoT Using Ensemble Classifiercited by 1

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