Reducing a search space for item identification using machine learning

A search space reduction method, comprising:

• storing an encoded vector library, wherein the encoded vector library comprises a plurality of encoded vectors, wherein:
• each encoded vector comprises a plurality of values associated with at least one attribute of a first object;
• and
• each encoded vector is associated with an item identifier for the first object;
• receiving a first encoded vector for a second object, wherein the first encoded vector for the second object comprises a plurality of values that are associated with at least one attribute of the second object;
• receiving one or more attributes of the second object;
• removing one or more encoded vectors from the encoded vector library that are not associated with at least one attribute of the second object;
• comparing the first encoded vector to encoded vectors in the encoded vector library;
• identifying a second encoded vector in the encoded vector library that most closely matches the first encoded vector based at least in part upon the values of the first encoded vector;
• identifying a first item identifier in the encoded vector library that is associated with the second encoded vector;
• and
• outputting the first item identifier.

A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to:

• store an encoded vector library in a memory, wherein the encoded vector library comprises a plurality of encoded vectors, wherein:
• each encoded vector comprises a plurality of values associated with at least one attribute of a first object;
• and
• each encoded vector is associated with an item identifier for the first object;
• receive a first encoded vector for a second object, wherein the first encoded vector for the second object comprises a plurality of values that are associated with at least one attribute of the second object;
• receive one or more attributes of the second object;
• remove one or more encoded vectors from the encoded vector library that are not associated with at least one attribute of the second object;
• compare the first encoded vector to encoded vectors in the encoded vector library;
• identify a second encoded vector in the encoded vector library that most closely matches the first encoded vector based at least in part upon the values of the first encoded vector;
• identify a first item identifier in the encoded vector library that is associated with the second encoded vector;
• and
• output the first item identifier.