Natural Language Processing
Natural Language Processing (NLP) technology is used to analyze, understand, and generate human language. It involves the use of algorithms and machine learning models to process and interpret large amounts of natural language data, such as text and speech. NLP is used in various applications, including chatbots, language translation, sentiment analysis, and speech recognition.
NLP is also an essential tool in the development of automated systems for curating scholarly literature, as it enables the analysis of text and metadata to identify the most relevant publications for a given research project. Our research team is experimenting with different techniques and methods that can help the computer understand what each article is about, such as bag-of-words and named entity recognition, pre-processing such as named entity recognition and de-identification, and from state-of-the-art NLP models such as transformers to identify relevant studies based on keywords, authors or other criteria.
The goal is to create a system that can quickly and accurately find the articles that are most relevant for a specific research project.
