CPC G06F 16/24542 (2019.01) [G06F 16/9017 (2019.01); G06N 20/00 (2019.01)] | 20 Claims |
1. A method for decreasing data access time using a lookup table and a relationship table, the method comprising:
receiving a trained categorization machine learning model trained using training data including a plurality of training tables comprising attribute data corresponding to attribute forms having a one-to-one relationship with an attribute among a plurality of attributes or attribute related information not having a one-to-one relationship with an attribute among the plurality of attributes, in which the attribute forms are tagged as attribute forms and the attribute related information is tagged as attribute related information;
receiving a plurality of tables comprising a plurality of attributes and attribute data, the attribute data comprising attribute forms having a one-to-one relationship with an attribute among the plurality of attributes and attribute related information not having a one-to-one relationship with an attribute among the plurality of attributes;
identifying attributes and corresponding attribute data from each of the plurality of tables;
applying the trained categorization machine learning model to categorize each attribute data as an attribute form having a one-to-one relationship with an attribute among the plurality of attributes or an attribute related information not having a one-to-one relationship with an attribute among the plurality of attributes;
generating the lookup table based on the attributes and the corresponding attribute forms having a one-to-one relationship with an attribute among the plurality of attributes;
generating the relationship table based on the attributes and the corresponding attribute related information not having a one-to-one relationship with an attribute among the plurality of attributes;
receiving a query for attribute data; and
generating a query response based on at least one of the lookup table or the relationship table.
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