Data discovery solution for data curation

A method of validating a plurality of unvalidated patterns using a crowdsource-based application, wherein the plurality of unvalidated patterns associate a plurality of tags to a plurality of data elements from one or more data sources comprising:

• receiving training input, including:
• transmitting, via the crowdsource-based application, a first matching question to a first player of a plurality of players, wherein the first matching question is configured to solicit a first player response that matches a first data element to a first tag;
• receiving, via the crowdsource-based application, the first player response;
• and
• storing a first pattern to a database comprising a corpus of patterns, the first pattern corresponding to the first player response;
• validating the first pattern within the corpus of patterns, including:
• transmitting, via the crowdsource-based application, a second matching question to the first player, wherein the second matching question comprises a validator question corresponding to a plurality of past answers from a corresponding plurality of other players, wherein each past answer of the plurality of past answers includes a corresponding reliability score associated with a respective one of the plurality of other players;
• receiving, via the crowdsource-based application, a second player response to the second matching question from the first player;
• matching the second player response to one or more past answers of the plurality of past answers;
• and
• generating a reliability rating for the first player based on the one or more reliability scores corresponding to the one or more past answers matching the second player response;
• weighting the first pattern in the corpus of patterns based on the reliability rating of the first player;
• training an artificial intelligence model using the first pattern weighted based on the reliability rating of the first player;
• and
• updating the weighting of the first pattern after the reliability rating of the first player changes.

A system of generating a set of candidate patterns comprising:

• a processor;
• and
• a memory including an artificial intelligence model that is trained with a corpus of patterns, the memory further including instructions that when executed, cause the processor to:
• receive training input, including:
• transmitting, via a matching application, a first matching question to a first player of a plurality of players, wherein the first matching question is configured to solicit a response that matches a first data element of a dataset to a first tag;
• receiving, via the matching application, a first player response that matches the first data element to the first tag;
• and
• storing a first pattern to a database comprising a corpus of patterns, the first pattern corresponding to the first player response;
• validate the first pattern within the corpus of patterns, including:
• transmitting, via the matching application, a second matching question to the first player, wherein the second matching question comprises a validator question corresponding to at least one past answer;
• receiving, via the matching application, a second player response to the second matching question;
• and
• generating a reliability rating for the first player based on consistency of the second player response to the second matching question with the at least one past answer;
• weight the first pattern in the corpus of patterns based on the reliability rating of the first player;
• and
• train the artificial intelligence model using the first pattern weighted based on the reliability rating of the first player.