Finder is designed to suggest key topics in a corpus of scientific research papers.
Finder is built upon the BERTopic library, which leverages transformers to identify and classify the key themes and topics within a corpus of documents.
Identify relevant topics within a large collection of scientific papers
Gain insights into emerging trends and topics within a particular field
Build your own models: embeddings, dimensionality reduction, clustering, tokeniser, weighting scheme, representation tuning
Visualise the topics per class or over time; calculate the probability of each topic