Learning similarity of representations
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I am interested in a framework for learning the similarity of different input representations based on some common context. I have looked into word2vec, SVD and other recommender systems, which does more or less what I want. I want to know if anyone here has any experience or resources on a more generalized version of this, where I am able to feed in representations on different objects, and learn how similar they are.
For example: Say we have some customers we are sending different advertisements to, and I would like to create a system to map offers to customers. I am thinking in the lines of creating a customer representation, and a representation of the offers, and feeding them in parallel to a neural network that has a label of whether they acted on the advertisement or not. The idea is that I should be able to locate the best offer for any customer given these representations.
I have looked into siamese networks and word2vec, both are close to what I want. The problem differs slightly in that the for the siamese networks, there are identical parallel networks, which I don't want because my inputs are not equivalent. Word2vec type methodology is also close, but I would want a model to process the inputs on "both sides". A combination of the two, is kind of what I am looking for.
If anyone has any resources on a similar problem statement, I would be very interested in it.
Thanks
deep-learning recommender-system word2vec similarity
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$begingroup$
I am interested in a framework for learning the similarity of different input representations based on some common context. I have looked into word2vec, SVD and other recommender systems, which does more or less what I want. I want to know if anyone here has any experience or resources on a more generalized version of this, where I am able to feed in representations on different objects, and learn how similar they are.
For example: Say we have some customers we are sending different advertisements to, and I would like to create a system to map offers to customers. I am thinking in the lines of creating a customer representation, and a representation of the offers, and feeding them in parallel to a neural network that has a label of whether they acted on the advertisement or not. The idea is that I should be able to locate the best offer for any customer given these representations.
I have looked into siamese networks and word2vec, both are close to what I want. The problem differs slightly in that the for the siamese networks, there are identical parallel networks, which I don't want because my inputs are not equivalent. Word2vec type methodology is also close, but I would want a model to process the inputs on "both sides". A combination of the two, is kind of what I am looking for.
If anyone has any resources on a similar problem statement, I would be very interested in it.
Thanks
deep-learning recommender-system word2vec similarity
asked yesterday
user10283726user10283726
1
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am interested in a framework for learning the similarity of different input representations based on some common context. I have looked into word2vec, SVD and other recommender systems, which does more or less what I want. I want to know if anyone here has any experience or resources on a more generalized version of this, where I am able to feed in representations on different objects, and learn how similar they are.
For example: Say we have some customers we are sending different advertisements to, and I would like to create a system to map offers to customers. I am thinking in the lines of creating a customer representation, and a representation of the offers, and feeding them in parallel to a neural network that has a label of whether they acted on the advertisement or not. The idea is that I should be able to locate the best offer for any customer given these representations.
I have looked into siamese networks and word2vec, both are close to what I want. The problem differs slightly in that the for the siamese networks, there are identical parallel networks, which I don't want because my inputs are not equivalent. Word2vec type methodology is also close, but I would want a model to process the inputs on "both sides". A combination of the two, is kind of what I am looking for.
If anyone has any resources on a similar problem statement, I would be very interested in it.
Thanks
deep-learning recommender-system word2vec similarity
asked yesterday
user10283726user10283726
1
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am interested in a framework for learning the similarity of different input representations based on some common context. I have looked into word2vec, SVD and other recommender systems, which does more or less what I want. I want to know if anyone here has any experience or resources on a more generalized version of this, where I am able to feed in representations on different objects, and learn how similar they are.
For example: Say we have some customers we are sending different advertisements to, and I would like to create a system to map offers to customers. I am thinking in the lines of creating a customer representation, and a representation of the offers, and feeding them in parallel to a neural network that has a label of whether they acted on the advertisement or not. The idea is that I should be able to locate the best offer for any customer given these representations.
I have looked into siamese networks and word2vec, both are close to what I want. The problem differs slightly in that the for the siamese networks, there are identical parallel networks, which I don't want because my inputs are not equivalent. Word2vec type methodology is also close, but I would want a model to process the inputs on "both sides". A combination of the two, is kind of what I am looking for.
If anyone has any resources on a similar problem statement, I would be very interested in it.
Thanks
deep-learning recommender-system word2vec similarity
deep-learning recommender-system word2vec similarity
asked yesterday
user10283726user10283726
1
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
user10283726user10283726
1
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
user10283726user10283726
1
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
user10283726user10283726
1
asked yesterday
user10283726user10283726
1
1
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
user10283726 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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