Machine learning for automated organization system and method

A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:

• identifying a plurality of content from at least one source;
• categorizing a first portion of the plurality of content in a first feed category based on a first probabilistic model;
• categorizing a second portion of the plurality of content in a second feed category based on the first probabilistic model;
• receiving user feedback to change the categorization of a first content of the first portion of the plurality of content in the first feed category to the second feed category;
• generating a second probabilistic model based upon, at least in part, the user feedback;
• and
• reorganizing the categorization of a second content of the first portion of the plurality of content in the first feed category based upon, at least in part, the second probabilistic model.

A computing system including one or more processors and one or more memories configured to perform operations comprising:

• identifying a plurality of content from at least one source;
• categorizing a first portion of the plurality of content in a first feed category based on a first probabilistic model;
• categorizing a second portion of the plurality of content in a second feed category based on the first probabilistic model;
• receiving user feedback to change the categorization of a first content of the first portion of the plurality of content in the first feed category to the second feed category;
• generating a second probabilistic model based upon, at least in part, the user feedback;
• and
• reorganizing the categorization of a second content of the first portion of the plurality of content in the first feed category based upon, at least in part, the second probabilistic model.