Methods, systems, and media for generating and prioritizing relevant content in real-time data systems

A method for recommending content for publishing, the method comprising:

• receiving, using a hardware processor, content from one or more content sources;
• determining, using the hardware processor, a plurality of interests associated with a publishing entity;
• retrieving, using the hardware processor, a plurality of candidate content owned by the publishing entity, wherein the plurality of candidate content includes published candidate content and unpublished candidate content;
• determining, using the hardware processor, one or more term entities associated with either the received content or the candidate content;
• calculating, using the hardware processor, a term entity score for each of the one or more term entities based on a recency and a density at which the one or more term entities appear in one or more real-time information sources;
• calculating, using the hardware processor, a content item score for each of a plurality of content items by aggregating calculations, for each term entity, based on the term entity's respective term entity score and a frequency at which the term entity appears in the content item for which the content item score is calculated, wherein each of the plurality of content items comprises at least a portion of the received content or the candidate content;
• ranking, using the hardware processor, the plurality of candidate content owned by the publishing entity and the received content based on their respective content item scores and the determined plurality of interests;
• and
• recommending, using the hardware processor, a content item for publication to at least one of the one or more real-time information sources based on the ranking, wherein the content item comprises at least a portion of the received content or the candidate content.

A system for recommending content for publishing, the system comprising:

• a processor that is configured to:
• receive information identifying a plurality of content sources associated with a user account;
• receive content from the plurality of content sources;
• determine one or more term entities associated with the content;
• calculate a term entity score for each of the one or more term entities based on a recency and a density at which the one or more term entities appear in one or more real-time information sources;
• and
• calculate a content item score for each of a plurality of content items by aggregating calculations, for each term entity, based on the term entity's respective term entity score and a frequency at which the term entity appears in the content item for which the content item score is calculated, wherein each of the plurality of content items comprises at least a portion of the content;
• recommend a content item of the plurality of content items for publication to at least one of the one or more real-time information sources based on the content item scores for the plurality of content items.

A system for recommending content for publishing, the system comprising:

• a processor that is configured to:
• receive content from one or more content sources;
• determine a plurality of interests associated with a publishing entity;
• retrieve a plurality of candidate content owned by the publishing entity, wherein the plurality of candidate content includes published candidate content and unpublished candidate content;
• determine one or more term entities associated with either the received content or the candidate content;
• calculate a term entity score for each of the one or more term entities based on a recency and a density at which the one or more term entities appear in one or more real-time information sources;
• calculate a content item score for each of a plurality of content items by aggregating calculations, for each term entity, based on the term entity's respective term entity score and a frequency at which the term entity appears in the content item for which the content item score is calculated, wherein each of the plurality of content items comprises at least a portion of the received content or the candidate content;
• rank the plurality of candidate content owned by the publishing entity and the received content based on their respective content item scores and the determined plurality of interests;
• and
• recommend a content item for publication to at least one of the one or more real-time information sources based on the ranking, wherein the content item comprises at least a portion of the received content or the candidate content.

A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for recommending content for publishing, the method comprising:

• receiving information identifying a plurality of content sources associated with a user account;
• receiving content from the plurality of content sources;
• determining one or more term entities associated with the content;
• calculating a term entity score for each of the one or more term entities based on a recency and a density at which the one or more term entities appear in one or more real-time information sources;
• calculating, using the hardware processor, a content item score for each of a plurality of content items by aggregating calculations, for each term entity, based on the term entity's respective term entity score and a frequency at which the term entity appears in the content item for which the content item score is calculated, wherein each of the plurality of content items comprises at least a portion of the content;
• and
• recommending a content item of the plurality of content items for publication to at least one of the one or more real-time information sources based on the content item scores for the plurality of content items.

A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for recommending content for publishing, the method comprising:

• receiving content from one or more content sources;
• determining a plurality of interests associated with a publishing entity;
• retrieving a plurality of candidate content owned by the publishing entity, wherein the plurality of candidate content includes published candidate content and unpublished candidate content;
• determining one or more term entities associated with either the received content or the candidate content;
• calculating a term entity score for each of the one or more term entities based on a recency and a density at which the one or more term entities appear in one or more real-time information sources;
• calculating a content item score for each of a plurality of content items by aggregating calculations, for each term entity, based on the term entity's respective term entity score and a frequency at which the term entity appears in the content item for which the content item score is calculated, wherein each of the plurality of content items comprises at least a portion of the received content or the candidate content;
• ranking the plurality of candidate content owned by the publishing entity and the received content based on their respective content item scores and the determined plurality of interests;
• and
• recommending a content item for publication to at least one of the one or more real-time information sources based on the ranking, wherein the content item comprises at least a portion of the received content or the candidate content.