Video content analysis for automatic demographics recognition of users and videos
First Claim
1. A computer-implemented method for generating a user classifier model, the method comprising:
- for each viewer of a plurality of viewers of digital videos, the viewers including viewers from a plurality of different households, and for a demographic attribute;
identifying a value of the demographic attribute for the viewer;
identifying a period of time during which the viewer viewed digital videos via a video hosting service;
identifying a plurality of digital videos viewed by the viewer during the identified period of time;
for the identified period of time, determining a set of features corresponding to the viewed digital videos, the features comprising content features derived from audiovisual content of the plurality of digital videos viewed during the period, andview-block features related to a division of the plurality of digital videos into subsets of videos viewed within a threshold amount of time of each other; and
associating the determined set of features with the demographic attribute value; and
for each demographic attribute value of a plurality of the demographic attribute values identified for the demographic attribute, training, by a computer processor, a user classifier model for the value of the demographic attribute using the sets of features associated with the demographic attribute value as input for an ensemble classifier training algorithm.
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Abstract
A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics.
In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos.
In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.
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Citations
20 Claims
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1. A computer-implemented method for generating a user classifier model, the method comprising:
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for each viewer of a plurality of viewers of digital videos, the viewers including viewers from a plurality of different households, and for a demographic attribute; identifying a value of the demographic attribute for the viewer; identifying a period of time during which the viewer viewed digital videos via a video hosting service; identifying a plurality of digital videos viewed by the viewer during the identified period of time; for the identified period of time, determining a set of features corresponding to the viewed digital videos, the features comprising content features derived from audiovisual content of the plurality of digital videos viewed during the period, and view-block features related to a division of the plurality of digital videos into subsets of videos viewed within a threshold amount of time of each other; and associating the determined set of features with the demographic attribute value; and for each demographic attribute value of a plurality of the demographic attribute values identified for the demographic attribute, training, by a computer processor, a user classifier model for the value of the demographic attribute using the sets of features associated with the demographic attribute value as input for an ensemble classifier training algorithm. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein for generating a user classifier model, actions of the computer program instructions comprising:
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for each viewer of a plurality of viewers of digital videos, the viewers including viewers from a plurality of different households, and for a demographic attribute; identifying a value of the demographic attribute for the viewer; identifying a period of time during which the viewer viewed digital videos via a video hosting service; identifying a plurality of digital videos viewed by the viewer during the identified period of time; for the identified period of time, determining a set of features corresponding to the viewed digital videos, the features comprising; view-block features related to a division of the plurality of digital videos into subsets of videos viewed within a threshold amount of time of each other; and associating the determined set of features with the demographic attribute value; and training a user classifier model for a value of the demographic attribute using the sets of features associated with the demographic attribute value. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A computer system for generating a user classifier model, the system comprising:
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a computer processor; and a computer-readable storage medium having executable computer program instructions embodied therein that when executed by the computer processor perform actions comprising; for each viewer of a plurality of viewers of digital videos, the viewers including viewers from a plurality of different households, and for a demographic attribute; identifying a value of the demographic attribute for the viewer; identifying a period of time during which the viewer viewed digital videos via a video hosting service; identifying a plurality of digital videos viewed by the viewer during the identified period of time; for the identified period of time, determining a set of features corresponding to the viewed digital videos, the features comprising at least one feature selected from the group consisting of; distributions of attributes of the plurality of digital videos viewed during the period, and view-block features related to a division of the plurality of digital videos into subsets of videos viewed within a threshold amount of time of each other; and associating the determined set of features with the demographic attribute value; and training a user classifier model for a value of the demographic attribute using the sets of features associated with the demographic attribute value. - View Dependent Claims (18, 19, 20)
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Specification