Consumer Insights Analysis Using Word Embeddings

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• receive a request to identify k steps for an entity to acquire a target attribute in public sentiments, wherein the request comprising a name for the entity and an n-gram representing the target attribute;
• identify a first word embedding for the entity and a second word embedding for the target attribute, wherein each word embedding represents a semantic context of a corresponding n-gram as a point in a d-dimensional embedding space;
• determine a directional vector that connects from the first word embedding to the second word embedding in the embedding space;
• identify k word embeddings that corresponds to k points on the directional vector, respectively;
• and
• determine, for each of the k identified word embeddings, a corresponding n-gram, wherein each n-gram represents an attribute located along a path for the entity to the target attribute in the embedding space.

A system comprising:

• one or more processors;
• and
• one or more computer-readable non-transitory storage media coupled to one or more of the processors and comprising instructions operable when executed by one or more of the processors to cause the system to:
• receive a request to identify k steps for an entity to acquire a target attribute in public sentiments, wherein the request comprising a name for the entity and an n-gram representing the target attribute;
• identify a first word embedding for the entity and a second word embedding for the target attribute, wherein each word embedding represents a semantic context of a corresponding n-gram as a point in a d-dimensional embedding space;
• determine a directional vector that connects from the first word embedding to the second word embedding in the embedding space;
• identify k word embeddings that corresponds to k points on the directional vector, respectively;
• and
• determine, for each of the k identified word embeddings, a corresponding n-gram, wherein each n-gram represents an attribute located along a path for the entity to the target attribute in the embedding space.