Systems and methods for item-specific keyword recommendation

A computer-implemented method, comprising:

• receiving an item data structure including an item title;
• generating at least one item embedding by applying a first trained semantic mapping model to the item title, wherein the first trained semantic mapping model includes a first semantic mapping framework;
• comparing the at least one item embedding to a set of keyword embeddings representative of a set of platform-relevant keywords;
• selecting a set of item-specific recommended keywords from the set of platform-relevant keywords based on a similarity between the at least one item embedding and each embedding in the set of keyword embeddings;
• modifying the item title to include at least one of the set of item-specific recommended keywords;
• updating the item data structure to include the modified item title;
• receiving a search query;
• and
• generating an interface responsive to the search query, wherein the interface includes the item data structure and the modified item title.

A non-transitory computer-readable medium having instructions stored thereon, wherein the instructions, when executed by at least one processor, cause a device to perform operations comprising:

• receiving an item data structure including an item title;
• generating at least one item embedding by applying a first trained semantic mapping model to the item title, wherein the first trained semantic mapping model includes a first semantic mapping framework;
• generating a set of keyword embeddings for a set of platform-relevant keywords by applying a second trained semantic mapping model to each keyword in the set of platform-relevant keywords, wherein the second trained semantic mapping model includes the first semantic mapping framework;
• determining a pairwise distance between the at least one item embedding and each embedding in the set of keyword embeddings in vector space;
• selecting a set of item-specific recommended keywords from the set of platform-relevant keywords based on a similarity between the at least one item embedding and each embedding in the set of keyword embeddings, wherein the set of item-specific recommended keywords includes keywords associated with keyword embeddings located within a predetermined pairwise distance of the at least one item embedding in vector space;
• modifying the item title to include at least one item-specific recommended keyword in the set of item-specific recommended keywords;
• updating the item data structure to include the modified item title;
• receiving a search query;
• and
• generating an interface responsive to the search query, wherein the interface includes the item data structure and the modified item title.