Context and domain sensitive spelling correction in a database

A health tracking system comprising:

• a database configured to store a plurality of data records, each of the plurality of data records comprising at least a descriptive string and nutritional data regarding a respective consumable item;
• and
• a data processor in communication with the database, the data processor being configured to:
• filter the plurality of data records to identify a subset thereof, the subset comprising those records in which the respective descriptive strings have correct spellings of every word contained therein;
• generate, for each data record in the identified subset of the plurality of data records, a plurality of companion descriptive strings, each of the companion descriptive strings comprising an incorrect spelling of at least one word contained therein;
• train a machine learning model using pairs of descriptive strings, each pair of descriptive strings including (i) the descriptive string of a respective data record in the identified subset of the plurality of data records, and (ii) a corresponding one of the companion descriptive strings having at least one word thereof incorrectly spelled;
• receive a first descriptive string having at least one word thereof incorrectly spelled;
• and
• use the trained machine learning model to output a second descriptive string to replace the first descriptive string, the second descriptive string having a correct spelling of the at least one incorrectly spelled word.

A method of operating a health tracking system having a database configured to store a plurality of data records, each of the plurality of data records comprising at least a descriptive string and nutritional data regarding a respective consumable item, the method comprising:

• receiving a first descriptive string having at least one word thereof incorrectly spelled;
• generating a vector with the first descriptive string using a machine learning model;
• identifying a second descriptive string which has a correct spelling of the at least one incorrectly spelled word by applying the machine learning model to the generated vector;
• calculating a confidence factor regarding the second descriptive string using the machine learning model;
• when it is determined that the confidence factor exceeds a predetermined threshold, searching the database to identify a first subset of data records in the plurality of data records having descriptive strings that are similar to the second descriptive string;
• and
• when it is determined that the confidence factor is below the predetermined threshold, searching the database to identify a second subset of data records in the plurality of data records having descriptive strings that are similar to the first descriptive string.