NLP - Predict most appropriate answer from Utterance
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My goal is to predict the most appropriate answer from an utterance, in a group of 21 potential answers.
Example:
Utterance: How are you today?
Answers: Answer1, 2, ..., 21.
I have a training file with this format:
Utterance:
Answers: Good answer, wrong answer1, wrong answer2,..., wrong answer20.
My problem
For the first time, we have to make a prediction from a group of possible answers, and, thus, this is a MCQ form.
Any ideas how I could start the problem?
What I've done
For the moment, the only thing I did was to choose the answers from the 21 possible answers which had the highest cosine similarity with the utterance. (So, unsupervised). It's not that bad (24% against 1/21 at random), but I'm sure there are ways to make something really better.
What I don't want to do at first
Use a generative model which predicts a full sentence. I want to choose the best candidate amongs the 21 answers, and use the training file which can allow us to do supervised learning.
nlp chatbot
$endgroup$
add a comment |
$begingroup$
My goal is to predict the most appropriate answer from an utterance, in a group of 21 potential answers.
Example:
Utterance: How are you today?
Answers: Answer1, 2, ..., 21.
I have a training file with this format:
Utterance:
Answers: Good answer, wrong answer1, wrong answer2,..., wrong answer20.
My problem
For the first time, we have to make a prediction from a group of possible answers, and, thus, this is a MCQ form.
Any ideas how I could start the problem?
What I've done
For the moment, the only thing I did was to choose the answers from the 21 possible answers which had the highest cosine similarity with the utterance. (So, unsupervised). It's not that bad (24% against 1/21 at random), but I'm sure there are ways to make something really better.
What I don't want to do at first
Use a generative model which predicts a full sentence. I want to choose the best candidate amongs the 21 answers, and use the training file which can allow us to do supervised learning.
nlp chatbot
$endgroup$
add a comment |
$begingroup$
My goal is to predict the most appropriate answer from an utterance, in a group of 21 potential answers.
Example:
Utterance: How are you today?
Answers: Answer1, 2, ..., 21.
I have a training file with this format:
Utterance:
Answers: Good answer, wrong answer1, wrong answer2,..., wrong answer20.
My problem
For the first time, we have to make a prediction from a group of possible answers, and, thus, this is a MCQ form.
Any ideas how I could start the problem?
What I've done
For the moment, the only thing I did was to choose the answers from the 21 possible answers which had the highest cosine similarity with the utterance. (So, unsupervised). It's not that bad (24% against 1/21 at random), but I'm sure there are ways to make something really better.
What I don't want to do at first
Use a generative model which predicts a full sentence. I want to choose the best candidate amongs the 21 answers, and use the training file which can allow us to do supervised learning.
nlp chatbot
$endgroup$
My goal is to predict the most appropriate answer from an utterance, in a group of 21 potential answers.
Example:
Utterance: How are you today?
Answers: Answer1, 2, ..., 21.
I have a training file with this format:
Utterance:
Answers: Good answer, wrong answer1, wrong answer2,..., wrong answer20.
My problem
For the first time, we have to make a prediction from a group of possible answers, and, thus, this is a MCQ form.
Any ideas how I could start the problem?
What I've done
For the moment, the only thing I did was to choose the answers from the 21 possible answers which had the highest cosine similarity with the utterance. (So, unsupervised). It's not that bad (24% against 1/21 at random), but I'm sure there are ways to make something really better.
What I don't want to do at first
Use a generative model which predicts a full sentence. I want to choose the best candidate amongs the 21 answers, and use the training file which can allow us to do supervised learning.
nlp chatbot
nlp chatbot
asked 5 mins ago
nolw38nolw38
63
63
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add a comment |
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