| CPC G06F 16/953 (2019.01) | 20 Claims |
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1. A method comprising:
loading, by a processor, a predictive model, the predictive model including a first set of hidden layers;
loading, by the processor, a semantic model, the semantic model including a second set of hidden layers;
generating, by the processor, a tenant model by combining the first set of hidden layers from the predictive model with a newly initialized third set of hidden layers, the third set of hidden layers receiving, as input, an output of the first set of hidden layers;
loading, by the processor, a tenanted training data set comprising interactions of users with a network search application;
training, by the processor, the tenant model by biasing the first set of hidden layers with the second set of hidden layers by adjusting bias terms of the first set of neural network hidden layers with corresponding bias terms of the second set of neural network hidden layers and training weights of at least the third set of hidden layers using the tenanted training data set; and
building, by the processor, an embedding index using the tenant model.
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