A Search Engine for Scientific Publications: a Cybersecurity Case Study

TL;DR

This paper introduces a specialized search engine for scientific publications that combines information retrieval and reading comprehension techniques, demonstrating strong generalization across domains like cybersecurity and beyond.

Contribution

It presents a novel search engine integrating retrieval and comprehension algorithms, adaptable to various scientific fields, improving access to domain-specific research information.

Findings

Effective in cybersecurity domain

Shows strong generalization to other fields

Enhances research efficiency

Abstract

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.