Search and retrieval service for scientic articles on COVID-19

Abstract

The COVID-19 pandemic was a global health crisis that lasted until May 4, 2023, affecting millions of people and raising many questions about transmission, diagnosis, treatment, vaccine development, and viral pathogens. Unfortunately, misinformation created more socioeconomic damage than the disease itself. To address this problem, we have developed Cognitive Search, a user-friendly application service that uses the latest advances in Natural Language Processing (NLP) to retrieve information from CORD-19, a resource for scholarly articles on COVID-19 and related pathogens. This system uses a combination of Term-Frequency, Semantic Neural Research, and Hybrid Term-Neural algorithms to improve document retrieval performance. The Hybrid Term-Neural approach also considers temporal information in documents to provide more accurate search results. With an intuitive interface, this application can generate valuable insights to help combat outbreaks.