SYSTEM AND METHOD FOR INCREASING ACCURACY OF APPROXIMATING QUERY RESULTS USING NEURAL NETWORKS

A system and method for improving training of a recurrent neural network (RNN) to provide a response to a table-based database query is presented. The method includes: receiving a plurality of query pairs, each including a database query and a response, the response generated by executing the database query on a database; detecting a variable in each query; determining a variance of the variable; generating a subset of potential values for the detected variable based on the determined variance, wherein each potential value is different from the response of each query pair; generating a plurality of training queries, each training query based on a database query of a query pair of the plurality of query pairs and a corresponding potential value from the first subset; executing each training query to generate a training response; and training the RNN based on the plurality of training queries and a corresponding training response.