NLP-Powered Repository and Search Engine for Academic Papers: A Case Study on Cyber Risk Literature with CyLit

TL;DR

This paper introduces CyLit, an NLP-powered repository for cyber risk literature that automates retrieval, summarization, and clustering to improve research efficiency and insight discovery in a rapidly evolving field.

Contribution

The paper presents a novel NLP framework and CyLit system that enhance academic literature search, categorization, and trend tracking specifically for cyber risk research.

Findings

CyLit improves literature retrieval accuracy and relevance.

It provides distinctive insights compared to traditional survey methods.

The system significantly enhances research efficiency in cyber risk domain.

Abstract

As the body of academic literature continues to grow, researchers face increasing difficulties in effectively searching for relevant resources. Existing databases and search engines often fall short of providing a comprehensive and contextually relevant collection of academic literature. To address this issue, we propose a novel framework that leverages Natural Language Processing (NLP) techniques. This framework automates the retrieval, summarization, and clustering of academic literature within a specific research domain. To demonstrate the effectiveness of our approach, we introduce CyLit, an NLP-powered repository specifically designed for the cyber risk literature. CyLit empowers researchers by providing access to context-specific resources and enabling the tracking of trends in the dynamic and rapidly evolving field of cyber risk. Through the automatic processing of large volumes of data, our NLP-powered solution significantly enhances the efficiency and specificity of academic literature searches. We compare the literature categorization results of CyLit to those presented in survey papers or generated by ChatGPT, highlighting the distinctive insights this tool provides into cyber risk research literature. Using NLP techniques, we aim to revolutionize the way researchers discover, analyze, and utilize academic resources, ultimately fostering advancements in various domains of knowledge.