Multi-document usage doesn't work with MMR diversity changes

[emigre459]

When attempting to look at different keyphrase lists by adjusting diversity for the MMR similarity metric, I find that the keyphrases never change regardless of the diversity value used. The keyphrases' output is corrected when I take the exemplar document out of a list form and just feed it as a single documentPlease see below code and results (using the text snippet from the README tutorial):

Version with a single piece of text in a single-element list:

keywords = kw_model.extract_keywords(
    docs=[doc],
    keyphrase_ngram_range=(2,5),
    use_mmr=True,
    diversity=0.7,
    vectorizer=None
)

>>> [[('examples supervised learning example', 0.6984),
  ('supervised learning machine', 0.6989),
  ('supervised learning', 0.7035),
  ('examples supervised learning', 0.7041),
  ('supervised learning example', 0.7558)]]

Version with a single piece of text fed directly as just a single document:

keywords = kw_model.extract_keywords(
    docs=doc,
    keyphrase_ngram_range=(2,5),
    use_mmr=True,
    diversity=0.7,
    vectorizer=None
)

>>> [('supervised learning example', 0.7558),
 ('output pairs', 0.1079),
 ('reasonable way', 0.1529),
 ('object typically vector', 0.2502),
 ('value called supervisory signal', 0.3348)]

Looking at the code for KeyBERT.extract_keywords(), it appears this is intentional, as there aren't even MMR/MaxSum options for _extract_keywords_multiple_docs(). Is there a reason why these diversity-enhancing metrics can't be used in the multi-document scenario?

[MaartenGr]

This was indeed on purpose since MMR and MaxSum work on a individual-document level whereas the multiple_docs implementation compares matrices of embeddings. During that process, MMR and MaxSum cannot be executed as it would significantly slow down the application. If I were to implement that option, it would essentially be same as iterating over extract_keywords which defeats its purpose.

[MaartenGr]

Since this issue has been a while without activity, I'll be closing it for now. However, if you are still experiencing the issue or want to discuss it further, let me know!