Systems and methods for generating aggregated reviews

A computer implemented method, comprising:

• receiving review data associated with an item object in a database, wherein the review data includes one or more review features including one or more target keywords;
• selecting a subset of the review data based on a first selection criteria configured to select a first subset of the review data;
• generating a target keyword score for each respective target keyword of the one or more target keywords based on a polarity of the target keywords;
• selecting a subset of the target keywords each having a respective target keyword score based on a predetermined range of the target keyword scores;
• generating one or more target keyword summaries for each respective target keyword of the selected subset of the target keywords;
• generating an item object summary based on the one or more target keyword summaries using a summarization model;
• iteratively modifying the item object summary using a self-critique module based on at least one or more characteristics of the item object summary, wherein:
• the self-critique module includes one or more large language models configured to evaluate the at least one or more characteristics of the item object summary and adjust the item object summary in accordance with a determination that the at least one or more characteristics of the item object summary does not meet a first criteria;
• and
• generating a set of instructions to cause the item object summary to be displayed on a user interface.

A non-transitory computer-readable storage medium comprising executable instructions that, when executed by one or more processors of a computing device, cause the one or more processors to:

• receive review data associated with an item object in a database, wherein the review data includes one or more review features including one or more target keywords;
• select a subset of the review data based on a first selection criteria configured to select a first subset of the review data;
• generate a target keyword score for each respective target keyword of the one or more target keywords based on a polarity of the target keywords;
• select a subset of the target keywords each having a respective target keyword score based on a predetermined range of the target keyword scores;
• generate one or more target keyword summaries for each respective target keyword of the selected subset of the target keywords;
• generate an item object summary based on the one or more target keyword summaries using a summarization model;
• iteratively modify the item object summary using a self-critique module based on at least one or more characteristics of the item object summary, wherein:
• the self-critique module includes one or more large language models configured to evaluate the at least one or more characteristics of the item object summary and adjust the item object summary in accordance with a determination that the at least one or more characteristics of the item object summary does not meet a first criteria;
• and
• generate a set of instructions to cause the item object summary to be displayed on a user interface.