Semantic Double-Pass Merging for improved keyphrase generation

[qdrddr]

Does it makes sence to utilize SDPM algorythm for keyBERT? This basically looks similarity forward, and then for the second time looks backward. This can be applicable to the keyphrases to better group them and the second pass can remove or split the words in a keyphrase if its not close enough.

Double-pass merging approach first groups content by semantic similarity, then merges similar groups within a skip window, allowing it to connect related content that may not be consecutive in the text. This technique is particularly useful for documents with recurring themes or concepts spread apart.

Here is explanation of how this works. https://bitpeak.com/chunking-methods-in-rag-methods-comparison/ https://docs.chonkie.ai/chunkers/sdpm-chunker