New answers tagged natural-language-processing
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Current state of the art and datasets for combining NLP and CV?
Your question is very interesting !
Actually your example is about multimodal sarcasm detection, one of the last paper on this task (as far I know) is Detection of Sarcasm through Tone Analysis on ...
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Can I use Sentence-Bert to embed event triples?
Sentence-Bert can embed any chain of characters in english and create semantically related embeddings (or at least contextual character-based if the model is dealing with OOV).
Even if no one else did ...
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Compare Strings composed from 2-3 words using NLP/ML(Python)
You can use a model to create rich embeddings for example: sentence transformers and then use cosine similarity distance from sklearn with a threshold (at least 0.6) to create clusters of semantically-...
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What is the best way to create a vector representation (with fasttext) of a list of words?
Welcome to the community.
So basically you would like to come up with a single vector representation for each employer considering different skills that particular employer has?
If that is the case, I ...
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What is the best way to create a vector representation (with fasttext) of a list of words?
Something that might work is a Universal Sentence Encoder. It's not quite what you asked for, as it generates encodings directly from text, not from other word vectors, but it is designed for matching ...
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Is there a relationship between Computer Algebra and NLP?
Yes there is a relationship, but it's not an exact one like I think is envisioned in the question.
Fuzzy numbers and fuzzy logic translates natural language expressions into quantitative values and ...
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How to configure a neural network to selectively change only certain characters in a string?
You could wrap each RNN cell in a custom module that is an identity for consonants (output = input when the input is a consonant) and predicts the macronization of vowels (it outputs the result from ...
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Is there any way to train a regression model with negative values that is more stable?
A couple things you could try:
You could try normalizing your target variable, so that it's number of standard deviations from the mean, or mapped to [-1,1].
If you are using drop-out during training. ...
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