Systems and methods for intelligent, scalable, and cost-effective data categorization

A non-transitory computer readable medium including instructions that are executable by one or more processors of a system to cause the system to perform operations for content classification, the operations comprising:

• extracting information associated with a first instance of content associated with a first person accessed from a database;
• cleaning the extracted information based on contextual information associated with the first instance of the content by analyzing relationships using the contextual information between a first element and a second element distinct from the first element in the extracted information, wherein analyzing the relationships includes using a relationship distance based on the contextual information to determine a relevance of one or more elements of the extracted information for classification into a first set of categories, and wherein cleaning the extracted information comprises:
• removing or correcting a less-relevant element or typographical error, and
• confirming the removing or correcting by recalculating the relationship distance after the removing or correcting;
• classifying the cleaned information into the first set of categories in a database;
• determining a second set of categories based on information associated with the first person, wherein the information associated with the first person includes the cleaned information associated with the first instance of the content;
• aggregating the cleaned information associated with the first person using the second set of categories, wherein one or more keywords of the cleaned information are grouped into categories;
• determining a third set of categories of information associated with a group of people including the first person, wherein the information includes the information associated with the first person;
• and
• determining a fourth set of categories based on the third set of categories.

A method performed by a system for content classification, the method comprising:

• extracting information associated with a first instance of content associated with a first source;
• cleaning the extracted information based on contextual information associated with the first instance of the content by analyzing relationships using the contextual information between a first element and a second element distinct from the first element in the extracted information, wherein analyzing the relationships includes using a relationship distance based on the contextual information to determine a relevance of one or more elements of the extracted information for classification into a first set of categories, and wherein cleaning the extracted information comprises:
• removing or correcting a less-relevant element or typographical error, and
• confirming the removing or correcting by recalculating the relationship distance after the removing or correcting;
• classifying the cleaned information into the first set of categories;
• determining a second set of categories based on information associated with the first source;
• aggregating the cleaned information associated with the first source using the second set of categories, wherein one or more keywords of the cleaned information are grouped into categories;
• determining a third set of categories of information associated with a group of people including the first source, wherein the information includes the information associated with the first source;
• and
• determining a fourth set of categories based on the third set of categories.