Context and domain sensitive spelling correction in a database

A method of operating a health tracking system, the method comprising:

• accessing 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;
• filtering the plurality of data records to identify a subset thereof, the subset comprising those records in which the respective descriptive strings have a first type of spelling of every word contained therein;
• generating, 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 one of a second type of spelling of at least one word contained therein;
• training 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 with the second type of spelling;
• receiving a descriptive string for a first data record having at least one word thereof with the second type of spelling and a second character sequence, the first data record comprising nutritional data regarding a consumable item;
• using the trained machine learning model to identify a substitute descriptive string to replace the received descriptive string for the first data record, the substitute descriptive string having the first type of spelling and a first character sequence of the at least one word instead of the second type of spelling and the second character sequence;
• calculating a confidence factor regarding the substitute descriptive string using the machine learning model;
• and
• when it is determined that the calculated confidence factor exceeds a predetermined threshold:
• modifying the first data record by replacing the first descriptive string with the substitute descriptive string;
• and
• storing the modified first data record in a database.

A non-transitory computer-readable medium comprising instructions which, when executed on a processor, cause the processor to:

• access 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;
• filter the plurality of data records to identify a subset thereof, the subset comprising those records in which the respective descriptive strings have a first type of spelling 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 one of a second type of spelling of at least one word contained therein;
• access a trained machine learning model trained 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 with the second type of spelling;
• receive a descriptive string for a first data record having at least one word thereof with the second type of spelling and a second character sequence, the first data record comprising nutritional data regarding a consumable item;
• use the trained machine learning model to identify a substitute descriptive string to replace the received descriptive string for the first data record, the substitute descriptive string having the first type of spelling and a first character sequence of the at least one word instead of the second type of spelling and the second character sequence;
• calculate a confidence factor regarding the substitute descriptive string using the machine learning model;
• and
• when it is determined that the calculated confidence factor exceeds a predetermined threshold:
• modify the first data record by replacing the descriptive string with the substitute descriptive string;
• and
• store the modified first data record in a database.