5. The computer-implemented method of claim 1 further comprising constructing a plurality of value-word pairs for a product attribute, each value-word pair comprising a respective product attribute value associated with a corresponding comment word.
1. A computer-implemented method for providing an interactive shopping advisor, the method comprising: configuring a plurality of long short term memory modules as a recurrent neural network, wherein the plurality of long short term memory modules are each provided with one or more respective gates for determining when a corresponding input value of a plurality of input values should persist in memory, and when the corresponding input value should comprise an output value; receiving, by the recurrent neural network, a natural language query for a product search, wherein each respective long short term memory module of the plurality of long short term memory modules receives a corresponding word from the natural language query; generating, by the recurrent neural network, an initial product recommendation from the natural language query; receiving, by the recurrent neural network, a natural language preference parameter for refining the product search; mapping, by the recurrent neural network, the natural language preference parameter to a product attribute value for the product search; identifying, by the recurrent neural network, an adjustment orientation of the product attribute value from the natural language preference parameter; and applying, by the recurrent neural network, the adjustment orientation to the natural language query to provide a refined product recommendation for the product search by determining, for each of the one or more respective gates, when the corresponding input value should persist in memory, and when the corresponding input value should comprise an output value.