I'm using the universal-sentence-encoder-large (Transformer Model) encoding process for embedding and then using the embedding for Clustering - Basically for unsupervised learning.

I want to get the top features / words which are contributing to the resultant clusters, in order to define the cluster or name the cluster in the business aspect with the help of the words contributing effectively for the cluster. Is there any way to do this using the universal-sentence-encoder-large?

where can I actually find the usage of universal-sentence-encoder-large's functions, like,

  • Fucntions:
    • embed.export()
    • embed.get_attached_message()
    • embed.get_input_info_dict()
    • embed.variable_map()
    • embed.variables()
    • embed.get_signature_names()**

Any help is hugely appreciated!

Thanks Arav

  • $\begingroup$ I am also looking for the same. $\endgroup$ – Problem_Solver23 Feb 18 '19 at 10:33

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