Class-based Term Frequency-Inverse Document Frequency; used by BERTopic for clearer topic representation and selection of important terms per cluster.
c-TF-IDF stands for Class-based Term Frequency-Inverse Document Frequency. It is a key component of the BERTopic algorithm.
This weighting scheme is used to refine the clusters created by HDBSCAN. Unlike models like Top2Vec, which rely mainly on semantic embeddings, BERTopic uses c-TF-IDF to highlight the most representative words for each topic. This results in clear topic words and yielding easily interpretable topics, giving BERTopic richer modeling capabilities.
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