Abstract: System and methods are disclosed herein for creating interaction path records using time thresholds between interaction paths. The system retrieves the time threshold and a plurality of user interaction records that each include a timestamp. The system sorts the plurality of user interaction records based on the timestamp. The system then identifies the path-start record as being separated from a prior interaction by an amount of time that exceeds the time threshold. The system identifies the path-end record as being separated from a subsequent interaction by an amount of time that exceeds the time threshold. The system creates an interaction path record, stores that records, and generates a summary with information about the path.

Abstract: System and methods are disclosed herein for creating interaction path records using time thresholds between interaction paths. The system retrieves the time threshold and a plurality of user interaction records that each include a timestamp. The system sorts the plurality of user interaction records based on the timestamp. The system then identifies the path-start record as being separated from a prior interaction by an amount of time that exceeds the time threshold. The system identifies the path-end record as being separated from a subsequent interaction by an amount of time that exceeds the time threshold. The system creates an interaction path record, stores that records, and generates a summary with information about the path.

Abstract: Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.

Abstract: Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.

Abstract: Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.

Abstract: System and methods are disclosed herein for creating interaction path records using time thresholds between interaction paths. The system retrieves the time threshold and a plurality of user interaction records that each include a timestamp. The system sorts the plurality of user interaction records based on the timestamp. The system then identifies the path-start record as being separated from a prior interaction by an amount of time that exceeds the time threshold. The system identifies the path-end record as being separated from a subsequent interaction by an amount of time that exceeds the time threshold. The system creates an interaction path record, stores that records, and generates a summary with information about the path.

Abstract: Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.

Abstract: Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.

Abstract: System and methods are disclosed herein for creating interaction path records using time thresholds between interaction paths. The system retrieves the time threshold and a plurality of user interaction records that each include a timestamp. The system sorts the plurality of user interaction records based on the timestamp. The system then identifies the path-start record as being separated from a prior interaction by an amount of time that exceeds the time threshold. The system identifies the path-end record as being separated from a subsequent interaction by an amount of time that exceeds the time threshold. The system creates an interaction path record, stores that records, and generates a summary with information about the path.

Abstract: System and methods are disclosed herein for creating interaction path records using time thresholds between interaction paths. The system retrieves the time threshold and a plurality of user interaction records that each include a timestamp. The system sorts the plurality of user interaction records based on the timestamp. The system then identifies the path-start record as being separated from a prior interaction by an amount of time that exceeds the time threshold. The system identifies the path-end record as being separated from a subsequent interaction by an amount of time that exceeds the time threshold. The system creates an interaction path record, stores that records, and generates a summary with information about the path.