- Number
- 10733626
- Published
- 2020-08-04
- Filed
- 2017-09-29
- Assignee
- DISNEY ENTERPRISES, INC.
- Inventors
- Somaya; Vikram, Srivastava; Ajit Kumar, Parr; Molly, Coleman; Sophie M., Chattleton; Christen Johnson, Keating; Scott T.
- CPC
- G06Q30/0631; G06Q30/0251
- Verdict
- Set aside ad-tech audience segmentation, business
- Source
- Google Patents · FreePatentsOnline
Abstract
A system and method for real-time generation of segments for a computerized decision system provides an event segment list to a decision engine. The event segment list is generated based on consumer affinities determined from consumer data and modeled data on that consumer's consumption and geo-location. The consumer affinities are used in a query to obtain current events related to the consumer's affinities. The current events are associated with generic events, which together are included in the event segment list, which is delivered to the decision engine and used to make a decision based on the event segment list and specified decision criteria.
Background
BACKGROUND(1) Computerized systems for generating data segments for use in decision systems are known. These systems, however, lack the ability to generate data segments in real time that reflect accurate information about a user's condition, including a combination of user-disclosed data, user-inferred data, and user situation/activity data. Prior systems use techniques such as internet-based cookie-level user attributes, manual content-based targeting, and manual event targeting to make decisions that may be used to generate recommendations, target messages, or take other actions customized to users(2) Audience targeting using cookie-level audience attributes from first party or third party sources has been used to target messages to an individual online. Content targeting, such as directing messages to consumers of certain types of content (e.g., football games) has been done manually by choosing to schedule advertisements or display other messages during such programming. Manual event targeting has been performed by predetermining a one-off event like a win of a given game and manually allocating creative options based on the outcome once the outcome is known.(3) Targeting in a television environment is generally limited to digital solutions and non-1:1 environments. Current systems are not capable of such automated, real-time targeting or customization at scale, requiring manual changes at a production switchboard.(4) Prior art systems are not designed to address the spe
Claims
1. A computer-based method for generating a real-time data segment list file for use by a computer-based decision engine to make a real-time decision based on real-time events and consumer-specific real-time data segments in the real-time data segment list file, comprising: receiving a data segment list file request from the decision engine; generating a list of consumer primary affinities based on at least one of consumer-declared affinities data, consumer consumption data, and consumer geolocation data; determining a relevant time window for relevant current events; generating a list of current event real-time data segments occurring during the relevant time window that relate to the consumer primary affinities, based on current event real-time data segments received from at least one event data source; retrieving a list of generic event data segments indicative of generic events, having a corresponding predetermined predicted real-time emotional state of the consumer and a corresponding predetermined emotion duration time, associated with each generic event dynamically associating by the computer each current event real-time data segment for each real-time event with at least one of the predetermined generic event data segments, the predetermined generic event data segments having at least the corresponding predicted real-time emotional state of the consumer and the corresponding emotion duration time; creating by the computer the real-time data segment list file using results of the associating, such that each real-time event has at least one generic event data segment having the corresponding predicted real-time emotional state of the consumer and the corresponding emotion duration time associated with the generic event; sending by the computer the real-time data segment list file, including at least the predicted real-time emotional state of the consumer and a corresponding emotion duration time, to the decision engine for use in making an accurate real-time decision regarding content to be delivered to the consumer, the response time from receiving the data segment list file request to sending the data segment list file being less than 500 milliseconds; and generating by the decision engine, in response to receiving the data segment list file, a recommendation of content to be consumed by the consumer or a selection of an advertisement to be shown to the consumer, the content recommendation or advertisement selection being based at least on the predicted real-time emotional state of the consumer and the corresponding emotion duration time.
11. A computer-based method for generating a real-time data segment list file for use by a computerized decision engine to make a real-time decision based on current sports real-time events and sports-related consumer-specific real-time data segments, comprising: receiving a sports-related data segment list file request from the decision engine; generating a list of consumer primary team fan affinities based on at least one of consumer-declared fan affinities data, consumer sports content consumption data, and consumer geolocation data; determining a relevant time window for relevant current sports events; generating a list of current sports event real-time data segments occurring during the relevant time window that relate to the consumer primary team fan affinities, based on current sports event real-time data segments received from at least one sports event data source; retrieving a list of generic sports event data segments indicative of generic sports events, having a corresponding predetermined predicted real-time emotional state of the consumer and a corresponding predetermined emotion duration time, associated with each generic sports event; dynamically associating by the computer each current sports event real-time data segment for each real-time event with at least one of the predetermined generic sports event data segments, the predetermined generic sports event data segments having at least the corresponding predicted real-time emotional state of the consumer and the corresponding emotion duration time; creating by the computer the real-time data segment list file using results of the associating, such that each real-time event has at least one generic event data segment having the corresponding predicted real-time emotional state of the consumer and the corresponding emotion duration time associated with the generic event; sending by the computer the real-time data segment list file, including at least the predicted real-time emotional data of the consumer and a corresponding emotion duration time, to the decision engine for use in making an accurate real-time decision regarding content to be delivered to the consumer, the response time from receiving the data segment list file request to sending the data segment list file being less than 500 milliseconds; and generating by the decision engine, in response to receiving the data segment list file, a recommendation of content to be consumed by the consumer or a selection of an advertisement to be shown to the consumer, the content recommendation or advertisement selection being based at least on the predicted real-time emotional state of the consumer and the corresponding emotion duration time.
15. A computer-based method for generating a real-time data segment list file for use by a computer-based decision engine to make a real-time decision based on real-time events and consumer-specific real-time data segments in the real-time data segment list file, comprising: receiving a data segment list file request from the decision engine; generating a list of consumer primary affinities based on at least one of consumer-declared affinities data, consumer consumption data, and consumer geolocation data; determining a relevant time window for relevant current events; generating a list of current event real-time data segments occurring during the relevant time window that relate to the consumer primary affinities, based on current event real-time data segments received from at least one event data source; retrieving a list of generic event data segments indicative of generic events, having a corresponding predetermined predicted real-time emotional state of the consumer associated with each generic event; dynamically associating by the computer each current event real-time data segment for each real-time event with at least one of the predetermined generic event data segments, the predetermined generic event data segments having at least the corresponding predicted real-time emotional state of the consumer; creating by the computer the real-time data segment list file using results of the associating, such that each real-time event has at least one generic event data segment having the corresponding predicted real-time emotional state of the consumer associated with the generic event; sending by the computer the real-time data segment list file, including at least the predicted real-time emotional state of the consumer, to the decision engine for use in making an accurate real-time decision regarding content to be delivered to the consumer, the response time from receiving the data segment list file request to sending the data segment list file being less than 500 milliseconds; and generating by the decision engine, in response to receiving the data segment list file, a recommendation of content to be consumed by the consumer or a selection of an advertisement to be shown to the consumer, the content recommendation or advertisement selection being based at least on the predicted real-time emotional state of the consumer.