Enhanced PTID prediction and accurate fitment using a PTID understanding model

A computer-implemented method comprising:

• tokenizing a query into tokens;
• transforming the tokens into embeddings;
• passing the embeddings through a classification layer of a Bidirectional Encoder Representations from Transformers (BERT) model to produce log its;
• applying a sigmoid function to convert the log its into a probability vector for Part Terminology Identifiers (PTIDs) associated with one or more predetermined domains;
• filtering the probability vector to retain PTIDs based on respective probabilities that are at least equal to a predetermined probability threshold, wherein a sum of the respective probabilities is equal to a predetermined sum value;
• ranking the PTIDs based on their respective probabilities;
• applying business logic to the ranked PTIDs using a PTID Understanding Model to determine a final result that is output to a fitment service, wherein the PTID Understanding Model is pretrained to trigger at least one of a fitment determination process or a query results filter process for the one or more predetermined domains when the final result is output as valid,
• wherein the business logic comprises:
• when a top ranked PTID is invalid and a respective probability is at least equal to a predetermined confidence level, the final result is output as invalid;
• when the top ranked PTID is valid and is at least equal to the predetermined confidence level, or when the top ranked PTID is invalid but the respective probability is less than the predetermined confidence level, a sum of all the respective probabilities for valid ranked PTIDs that are included in the probability vector, as filtered, is determined;
• and
• when the sum of all the respective probabilities of the valid ranked PTIDs is at least equal to a predetermined cutoff value, the valid ranked PTIDs are included in the final result, wherein the final result is output as valid.

A non-transitory computer-readable medium storing computing instructions that, when executed on a processor, cause the processor to perform operations comprising a computer-implemented method, the computer-implemented method comprising:

• tokenizing a query into tokens;
• transforming the tokens into embeddings;
• passing the embeddings through a classification layer to produce log its;
• applying a sigmoid function to convert the log its into a probability vector for Part Terminology Identifiers (PTIDs) associated with one or more predetermined domains;
• filtering the probability vector to retain PTIDs based on respective probabilities that are at least equal to a predetermined probability threshold, wherein a sum of the respective probabilities is equal to a predetermined sum value;
• ranking the PTIDs based on their respective probabilities;
• applying business logic to the ranked PTIDs using a PTID Understanding Model to determine a final result that is output to a fitment service, wherein the PTID Understanding Model is pretrained to trigger at least one of a fitment determination process or a query results filter process for the one or more predetermined domains when the final result is output as valid,
• wherein the business logic comprises:
• when a top ranked PTID is invalid and a respective probability is at least equal to a predetermined confidence level, the final result is output as invalid;
• when the top ranked PTID is valid and is at least equal to the predetermined confidence level, or when the top ranked PTID is invalid but the respective probability is less than the predetermined confidence level, a sum of all the respective probabilities for valid ranked PTIDs that are included in the probability vector, as filtered, is determined;
• and
• when the sum of all the respective probabilities of the valid ranked PTIDs is at least equal to a predetermined cutoff value, the valid ranked PTIDs are included in the final result, wherein the final result is output as valid.