Zeer zorgwekkende stoffen in het milieu (deel 3) – Literature mining

Natural Language Processing (NLP) is a subfield of computer science and artificial intelligence that deals with the interaction between machines and human languages. It enables machines to try to understand, interpret, and generate human language, making it a powerful tool for various applications. One of the areas where NLP has shown
potential is in Literature Mining, which typically is the automated process of extracting relevant and valuable information from large volumes of written texts. It involves analyzing the structure and content of written texts to identify named entities and relationships of information.
NLP is a key component of automated text interpretation. By using NLP techniques, machines can analyze written texts, identify key concepts, and extract relevant information. One of the primary applications of NLP in Literature Mining is in text classification, which involves categorizing written texts into different categories based on their content. Another application of NLP in Literature Mining is Named Entity Recognition (NER), which involves identifying and categorizing information into pre-defined classes, e.g., locations of interest, names of chemical components.
Recently, there have been significant advances in NLP technology, particularly with the development of Generative Pre-trained Transformer (GPT) models. These models are capable of interpreting and generating text at a near-human level, making them potentially useful in Literature Mining. For example, GPT can potentially be used to analyze large volumes of texts, find information, and generate summaries automatically, which can save researchers a significant amount of time and effort. As such, the integration of GPT technology into Literature Mining has the potential to further advance many fields.

Natural Language Processing (NLP) en Large Language Models (LLM) kunnen een cruciale rol vervullen bij literatuuronderzoek door het analyseren van geschreven teksten te automatiseren, belangrijke concepten te identificeren en relevante informatie te extraheren. Er is een benadering ontwikkeld voor literatuuronderzoek met behulp van NLP en LLM’s door NLP in te zetten bij het zoeken naar informatie over chemische verbindingen. Dit rapport beschrijft de methode die wordt gebruikt voor geautomatiseerd downloaden van artikelen en informatie- extractie met behulp van NLP