Semantic Keywords And Keyphrases Extraction With KeyBERT

It is also possible to use different embedding models for multilingual tasks in case you might want to use other languages. N-gram words/expressions retrieval: from the same previous document, keywords and key phrases are extracted using the n-gram approach. We get keywords when the n-gram range is (1, 1). N-grams embedding: each one of those n-grams is then embedded using the same embedding model as the one used for the original document. Cosine Similarity search: amongst the previous set of words/phrases/expressions, the most similar ones to the input document are selected using the cosine similarity metrics.