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Look at different methods of search.
- https://github.com/google-research/google-research/tree/master/scann
- https://github.com/facebookresearch/faiss
- https://github.com/nmslib/hnswlib
- http…
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It seems that the weighting scheme TF-IDF(MM) is hardly ever selected for "Citations and Terms"
![image](https://f.cloud.github.com/assets/2410381/2109122/1f0c13a2-8feb-11e3-9d42-8693fd1ea2d8.png)
s…
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can use built in NLTK version based on:
https://github.com/learntextvis/code-samples/blob/master/python/get_tfidf_on_files.py
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Hello!
I have been using the merged models to avoid RAM limitations.
After merging my models into a new model, I found that there are no representative documents in model.get_topic_info() and also …
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I wonder which approach would be recommended in the following scenario and if there is a way to combine the advantages of TF-IDF and CrossEncoders in a hybrid model?
I want to detect similar text d…
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Hi, I tried to implement TF-IDF (Term Frequency - Inverse Document Frequency) in Morel, and I almost managed to get it to work.
The formula that is used to compute tf-idf is defined as follows:
…
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Hi,
I want to check if combination with tf-idf weights and tokens embeddings is better representation for my use case/data(I would love to know what you think about it).
Searching for implementation…
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Hi,
I am trying to add a two word phrase that we can search for.
Eg.
"meet me"
tf-idf should return weight(positive) for this only when both the terms are search.
So, if user searches for 'me…