Query analysis using deep neural net classification

A method for answering a query comprising:

• receiving an intelligence data store comprising a plurality of data objects comprising previous queries and associated one or more patterns with dispositions associated with the previous queries and associated one or more patterns;
• receiving a current data object with a current query and at least one knowledge graph;
• identifying, by a feature identifier, one or more patterns in the at least one knowledge graph;
• comparing, by a comparison engine, using a deep neural net, the previous queries and associated one or more patterns with the current query and identified one or more patterns of the current data object;
• classifying, by a classification engine, the plurality data objects from the intelligence data store based on a closeness of the current query and identified one or more patterns with each of the previous queries and associated one or more patterns;
• and
• identifying, by the classification engine, potential dispositions based on the classification of the plurality of data objects.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:

• receiving an intelligence data store comprising a plurality of data objects comprising previous queries and associated one or more patterns with dispositions associated with the previous queries and associated one or more patterns;
• receiving a current data object with a current query and at least one knowledge graph;
• identifying, by a feature identifier, one or more patterns in the at least one knowledge graph;
• comparing, by a comparison engine, using a deep neural net, the previous queries and associated one or more patterns with the current query and identified one or more patterns of the current data object;
• classifying, by a classification engine, the plurality data objects from the intelligence data store based on a closeness of the current query and identified one or more patterns with each of the previous queries and associated one or more patterns;
• and
• identifying, by the classification engine, potential dispositions based on the classification of the plurality of data objects.