Kumar S, J.K.Anand Kumar, M.2026-02-0620232023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023, 2023, Vol., , p. -https://doi.org/10.1109/ICCCNT56998.2023.10308313https://idr.nitk.ac.in/handle/123456789/29379The process of extracting keyphrases from a document automatically, without any supervision, is referred to as Unsupervised Keyphrase Extraction. This method aims to produce a brief summary of the main content of the document. Embedding-based methods comprise computing similarity between candidate keyphrases and documents embeddings. In this paper, we find that filtering candidate keyphrases using graph-based techniques enriches frequent candidates which are reranked using embeddings. On comparing the proposed model to the current state-of-the-art unsupervised Keyphrase Extraction approaches across three KPE benchmarks, it was found that the proposed model outperformed them. © 2023 IEEE.BERTembeddingkeyphrase extractionsentence similarity