Clustering Lists of Words (Python)

Question

I have 54 lists consisting of words of varying lengths. For example:
1 = ["fly", "robot", "ketchup"].
2 = ["rain", "fly", "top", "jacket"].
....

I would like to cluster similar lists into groups based on the words in each list. The order of the words in the list does matter slightly but isn't the only criteria for a match. Any ideas? I was thinking of using BERT and then K-means clustering.

I want the lists to remain intact, just grouped/clustered.

Does this answer your question? clustering list of words in python — user3503711
– user3503711, Commented Sep 7, 2022 at 15:06
Not exactly. That question wants to cluster words in a list into clusters where I want to cluster the lists themselves. Leaving the lists intact but grouping them based on the words. Does that make sense? — Jule
– Jule, Commented Sep 7, 2022 at 15:08

José Cañete · Accepted Answer · 2022-09-15 02:38:29Z

0

I think BERT + K-Means is a good approach. Since the order of the words matter I would just treat each list as a sentence and instead of using just BERT I would use SentenceBERT which is usually better for clustering tasks.

Here you have a good tutorial from the original SentenceBERT documentation.

answered Sep 15, 2022 at 2:38

José Cañete

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