NLP-Powered Repository and Search Engine for Academic Papers: A Case Study on Cyber Risk Literature with CyLit
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.
Code (0)
등록된 구현이 없습니다.
Tasks
SpecificitySimilar Papers 제목 키워드 기반
NLP Scholar: A Dataset for Examining the State of NLP Research
Google Scholar is the largest web search engine for academic literature that also provides access to rich metadata associated with the papers. The ACL Anthology (AA) is the largest repository of articles on Natural Langu…
ArticlesTracing Digital Footprints to Academic Articles: An Investigation of PeerJ Publication Referral Data
In this study, we propose a novel way to explore the patterns of people's visits to academic articles. About 3.4 million links to referral source of visitors of 1432 papers published in the journal of PeerJ are collected…
ArticlesTalk to Papers: Bringing Neural Question Answering to Academic Search
We introduce Talk to Papers, which exploits the recent open-domain question answering (QA) techniques to improve the current experience of academic search. It's designed to enable researchers to use natural language quer…
Natural Language QueriesOpen-Domain Question AnsweringQuestion Answeringpaper2repo: GitHub Repository Recommendation for Academic Papers
GitHub has become a popular social application platform, where a large number of users post their open source projects. In particular, an increasing number of researchers release repositories of source code related to th…
Recommendation SystemsAutoP2C: An LLM-Based Agent Framework for Code Repository Generation from Multimodal Content in Academic Papers
Machine Learning (ML) research is spread through academic papers featuring rich multimodal content, including text, diagrams, and tabular results. However, translating these multimodal elements into executable code remai…
Code Generation