Predictive feedback engine for improving search relevance in a tenant configurable hybrid search system

A non-transitory computer-readable storage medium for tangibly storing computer program instructions capable of being executed by a computer processor, the computer program instructions defining steps of:

• loading a predictive model, the predictive model including a first set of hidden layers;
• loading a semantic model, the semantic model including a second set of hidden layers;
• generating a tenant model using the first set of hidden layers and a third set of hidden layers, the third set of hidden layers receiving, as input, an output of the first set of hidden layers;
• loading a tenanted training data set;
• training the tenant model by biasing the first set of hidden layers with the second set of hidden layers and training weights of at least the third set of hidden layers using the tenanted training data set;
• and
• building an embedding index using the tenant model.

A device comprising:

• a processor;
• and
• a storage medium for tangibly storing thereon logic for execution by the processor, the logic comprising instructions for:
• loading a predictive model, the predictive model including a first set of hidden layers;
• loading a semantic model, the semantic model including a second set of hidden layers;
• generating a tenant model using the first set of hidden layers and a third set of hidden layers, the third set of hidden layers receiving, as input, an output of the first set of hidden layers;
• loading a tenanted training data set;
• training the tenant model by biasing the first set of hidden layers with the second set of hidden layers and training weights of at least the third set of hidden layers using the tenanted training data set;
• and
• building an embedding index using the tenant model.