Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 1 of 13 Page ID #:11
`
`
`
`Exhibit A
`
`
`
`
`
`

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`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 2 of 13 Page ID #:12
`case Zizo'cv'llo‘r’a'JVS'JPR moment 1HIIII lllflfilllfllfflllmlll lllllflllfillll 11111111111111”
`
`USOlO728619B2
`
`(12) Un1ted States Patent
`(10) Patent No.:
`US 10,728,619 B2
`
`Johnson
`(45) Date of Patent:
`Jul. 28, 2020
`
`(54) SYSTEMS AND METHODS FOR PLAYBACK
`RESPONSIVE ADVERTISEMENTS AND
`PURCHASE TRANSACTIONS
`
`USPC ............................................................ 725/34
`See application file for complete search history.
`
`(71) Applicant: PUCs, LLC, Los Angeles, CA (US)
`
`(56)
`
`References Cited
`
`(72)
`
`Inventor: Charles Johnson, Los Angeles, CA
`(Us)
`(73) Assi nee‘ PUCs LLC Los An eles CA (US)
`g
`'
`3
`a
`g
`3
`
`( * ) Notice:
`
`Subject to any disclaimer, the term Ofthis
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 0 days.
`
`(21) Appl. No.: 16/228,607
`.
`.
`Ffled‘
`
`(22)
`
`(65)
`
`Dec“ 20’ 2018
`.
`.
`.
`PHOF Plibllcatlon Data
`
`US 2019/0208273 A1
`
`JUL 4, 2019
`
`Related US. Application Data
`
`6,057,872 A *
`
`U-S- PATENT DOCUMENTS
`5,758,257 A *
`5/1998 Herz .................... G06Q 20/383
`348/E7'056
`5/2000 Candelore .......... H04N 7/17318
`725/23
`9/2002 Eldering ................ G06Q 30/02
`3/2007 Fish ....................... G06Q 10/10
`348/E7.07
`2/2013 Ramaswamy ......... H04H 20/14
`_
`725/ 14
`7/2013 Xav1er
`................... G06Q 30/00
`705/261
`7/2014 Rosenberg ......... G06Q 30/0241
`705/1459
`.......... H04N 21/2668
`5/2017 Czeck, Jr.
`6/2017 Natarajan ........ H04N21/25816
`8/2017 Meoded ............. G06Q 30/0264
`(Continued)
`
`6,457,010 Bl *
`7,194,757 B1*
`
`8,381,241 B2 *
`
`8,478,664 B1 *
`
`8,775,256 B2*
`
`9,654,815 B2 *
`9,674,565 B2 *
`9,743,136 B2 *
`
`(60)
`
`Prov151onal application No. 62/612,588, filed on Dec.
`3 l , 2017.
`
`Primary Examiner 7 Michael B. Pierorazio
`(74) Attorney, Agent, or Firm 7 Fish IP Law, LLP
`
`(51)
`
`Int. Cl.
`H04N 7/10
`H04N 21/458
`H04N 21/44
`H041V 21/478
`H041V 21/466
`H04N 21/81
`
`(2006.01)
`(2011.01)
`(201101)
`(201101)
`(2011 ‘01)
`(2011.01)
`
`ABSTRACT
`(57)
`In a method for displaying tailored advertising in response
`to user media playback behavior, an ad engine detects media
`playback by a user. The ad engine retrieves an advertisement
`rule associated with the user. Following retrieval of the
`advertisement rule,
`the ad engine analyzes the content
`associated with the media playback and queues user tailored
`advertisements based on the analyzed content and the adver-
`tisement rule. The ad engine then displays an advertisement
`in response to detecting a pause in the media playback in a
`Content provider-based software application.
`
`12 Claims, 4 Drawing Sheets
`
`/ no
`
`(52) U-S- Cl-
`CPC ~~~~~ H04N 21/458 (201301); H04N 21/44016
`(201301); H04N 21/466 7 (201301); H04N
`21/47815 (201301); H04N 21/812 (201301)
`(58) Field Of Classification Search
`CPC ........... H04N 21/458; H04N 21/44016; H04N
`2l/47815; H04N 2l/4667; H04N 21/812;
`H04N 2l/2668; H04N 2l/6582; H04N
`2l/44204
`
`
`
`
`START
`
`v
`
`IDEN’HFYA USER
`
`
`\—
`RECEIVE USERDATA
`
`3
`
`02 \
`204
`
` v
`
`
`V
`
`206 a.
`
`POLICYFOR THE USER BASEDON
`\ DETERMINE AN ADVERTISEMENT
`USERDATA
`
`V
`\\ APPLYADVERTISEMENTPOLICY
`TOAVAILABLE ADWKI‘ISENENTS
`
`208
`
`#—
`
`ADVERTESEMENTS BASED ON
`2£0 1 COMP'LLEUSERRELEVANT
`ADVERTISEMENTPGLECY
`
`
`END
`
`
`
`

`

`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 3 of 13 Page ID #:13
`Case 2:20-cv-11056-JVS-JPR Document 1—1 Filed 12/04/20 Page 3 of 13 Page ID #:13
`
`US 10,728,619 B2
`
`Page 2
`
`(56)
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`9,788,079 B2 * 10/2017 Chand .................. H04N 21/812
`H04N 7/17318
`9,800,949 B2* 10/2017 Cansler
`
`5/2018 Harrison ......
`. H04N 21/233
`9,961,388 B2*
`
`5/2018 Garcia Navarro ...........................
`9,986,299 B2*
`H04N 21/4826
`................. H04N21/4662
`1/2019 Jamil
`10,178,436 B2*
`1/2019 Nguyen ............. H04N21/4331
`10,187,689 B2 *
`.. H04N 21/251
`10,462,508 B2* 10/2019
`
`8/2002 Shinohara ............. G06F 3/0481
`2002/0108114 A1*
`725/46
`9/2002 A130 .................... H04N 21/812
`725/109
`8/2003 Sender ................... G06Q 30/02
`705/1455
`2/2004 Hord ........................ H04N 5/76
`725/136
`4/2004 Messenger ............. G06Q 30/06
`2004/0079798 A1*
`235/381
`2004/0255322 A1* 12/2004 Meadows .......... H04N 7/17309
`725/23
`
`2003/0149618 A1*
`
`2004/0034874 A1*
`
`2002/0138848 A1*
`
`2005/0091069 A1*
`
`2005/0193416 A1*
`
`4/2005 Chuang ~~~~~~~~~~~~~~ G06Q 30/0207
`705/307
`9/2005 Przybylek ............ H04N 21/466
`725/53
`
`2007/0162951 A1*
`2007/0214473 A1*
`
`2008/0092181 A1 *
`
`2010/0030808 A1*
`
`2010/0158101 A1*
`
`2010/0205541 A1*
`
`8/2010 RApaport
`
`2012/0124618 A1 *
`
`7/2007 Rashkovskiy ....... H04H 20/106
`725/134
`9/2007 Barton ................. G11B 27/105
`725/28
`4/2008 Britt ..................... H04N 7/1675
`725/87
`2008/0282285 A1* 11/2008 Thomas ................... H04N 5/76
`725/32
`2/2010 Ress ...................... H04N 21/21
`709/227
`6/2010 Wu .................. H04N21/23424
`375/240.01
`............... G06Q 10/ 10
`715/753
`2011/0289538 A1* 11/2011 Begen ................... H04L 65/605
`725/107
`5/2012 Ruiz-Velasco ..... G06Q 30/0241
`725/32
`5/2013 R611 .................... H04N 21/2541
`2013/0139191 A1*
`/
`725/1
`/
`*
`62013 H30 ~~~~~~~~~~~~~~~~~~~ 11091217223593
`2013 0145383 A1
`*
`“014
`H04N21/722555jfi
`2014/0157295 A1
`3/2018
`H04N 21/4826
`2018/0063591 A1*
`2018/0367863 A1* 12/2018
`H04N 21/44204
`2019/0098352 A1*
`3/2019 Jung .................. H04N21/2668
`
`
`
`* cited by examiner
`
`

`

`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 4 of 13 Page ID #:14
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 4 of 13 Page ID #:14
`
`U.S. Patent
`
`Jul. 28, 2020
`
`Sheet 1 014
`
`US 10,728,619 B2
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`ADENG'ENE
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`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 5 of 13 Page ID #:15
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 5 of 13 Page ID #:15
`
`U.S. Patent
`
`Jul. 28, 2020
`
`Sheet 2 0f 4
`
`US 10,728,619 B2
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`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 6 of 13 Page ID #:16
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 6 of 13 Page ID #:16
`
`U.S. Patent
`
`Jul. 28, 2020
`
`Sheet 3 0f 4
`
`US 10,728,619 B2
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`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 7 of 13 Page ID #:17
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 7 of 13 Page ID #:17
`
`U.S. Patent
`
`Jul. 28, 2020
`
`Sheet 4 0f 4
`
`US 10,728,619 B2
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`

`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 8 of 13 Page ID #:18
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 8 of 13 Page ID #:18
`
`US 10,728,619 B2
`
`1
`SYSTEMS AND METHODS FOR PLAYBACK
`RESPONSIVE ADVERTISEMENTS AND
`PURCHASE TRANSACTIONS
`
`FIELD OF THE INVENTION
`
`The field of the invention is interactive media playback.
`
`BACKGROUND
`
`Conventional advertisements play at prearranged com-
`mercial breaks and are severely limited in their interactivity.
`Content from streaming websites often contains at least one
`advertisement break when one or more advertisements are
`
`played back. Often, these advertisements repeat as conven-
`tional systems fail to tailor the advertisements to the par-
`ticular user viewing the advertisement. Further, the adver-
`tisements in conventional streaming content have limited
`interactive elements,
`including, for example, skipping an
`advertisement or clicking a hyperlink to take you to a
`separate website.
`US. Patent Application Publication No. 2008/0282285 to
`Thomas discloses a method of substituting pause-time con-
`tent in place of media that is paused. Among other things,
`Thomas does not disclose analyzing the media content and
`user data to queue advertisements to over-the-top (OTT)
`internet signals. Additionally, Thomas does not contemplate
`the use of interactive advertisements that can work with a
`
`single user device or cooperatively with multiple user
`devices to receive user input and execute transactions
`directly from the interactive advertisement.
`US. Patent Application Pub. No. 2004/0034874 A1 to
`Hord discloses advertisement playback during trick mode
`functionality. However, Hord does not disclose the delivery
`of interactive advertisements. Further, Hord does not dis-
`close the queuing of advertisements prior to advertisement
`playback based on user data, media data, and advertisement
`data.
`
`Similarly to Hord, US. Patent Application Pub. No.
`2007/0162951 A1 to Rashkovskly discloses advertisement
`playback during paused content. However, Rashkovskly
`does not disclose the delivery of interactive advertisements.
`As with Hord, Rashkovskly also does not disclose the
`queuing of advertisements prior to advertisement playback
`based on user data, media data, and advertisement data.
`US. Pat. No. 8,775,256 to Rosenberg discloses a hard-
`ware implementation of pause ads and content delivery.
`Rosenberg integrates advertisement delivery into a piece of
`hardware (e.g., a set top box/device), and advertisements are
`served to that device and displayed from that device. How-
`ever, Rosenberg does not contemplate the delivery of con-
`ventional and/or interactive advertisements through soft-
`ware-based mediums, including, for example, audio delivery
`applications, long form content applications, and gaming
`applications.
`Thomas, Hord, Rashkovskly, Rosenberg, and all other
`extrinsic materials discussed herein are incorporated by
`reference to the same extent as if each individual extrinsic
`
`material was specifically and individually indicated to be
`incorporated by reference. Where a definition or use of a
`term in an incorporated reference is inconsistent or contrary
`to the definition of that term provided herein, the definition
`of that term provided herein applies and the definition of that
`term in the reference does not apply.
`Conventional advertisement systems can be improved by
`using user data, media data, and advertisement data to select
`one or more advertisements for playback during a partial or
`
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`complete pause in media playback. By using a wider array
`of data to make advertisement playback decisions,
`the
`present
`invention is an improvement over the prior art
`because it allows highly user and media-relevant advertise-
`ments to be played back during a partial or complete pause
`in media playback.
`Thus, there is still a need for systems and methods for
`improving advertisement playback based on user data,
`media data, and advertisement data.
`
`SUMMARY OF THE INVENTION
`
`Among other things, the inventive subject matter provides
`apparatus, systems, and methods for displaying tailored
`advertising in response to user media playback behavior.
`The inventive concept herein can be employed in a variety
`of applications, including, for example, long and short form
`video content, video game-based software content, and long
`and short form audio content. Conventional advertisement
`
`delivery systems do not contemplate the delivery of inter-
`active advertisements to any device through software appli-
`cations during pauses in content playback or interaction
`(e.g., pauses in playing video games). As such, the claimed
`invention improves upon the conventional advertisement
`delivery systems by enabling interactive advertisement
`delivery to software applications, which allows advertise-
`ment delivery to any software through any type of media
`playback device.
`Various resources, features, aspects and advantages of the
`inventive subject matter will become more apparent from
`the following detailed description of preferred embodi-
`ments, along with the accompanying drawing figures in
`which like numerals represent like components.
`The present invention advantageously allows advertise-
`ments to playback when media content is partially or com-
`pletely paused.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 is a functional block diagram illustrative a distrib-
`uted data processing environment.
`FIG. 2 is a schematic of a method of using user data to
`determine an advertisement policy for a user.
`FIG. 3 is a schematic of a method of compiling and
`initiating playback of advertisements in response to a media
`playback action.
`FIG. 4 is a schematic of a method of executing a trans-
`action via a media playback action initiated interactive
`advertisement.
`
`DETAILED DESCRIPTION
`
`In some embodiments, the numbers expressing quantities
`of ingredients, properties such as concentration, reaction
`conditions, and so forth, used to describe and claim certain
`embodiments of the invention are to be understood as being
`modified in some instances by the term “about.” Accord-
`ingly, in some embodiments, the numerical parameters set
`forth in the written description and attached claims are
`approximations that can vary depending upon the desired
`properties sought to be obtained by a particular embodiment.
`In some embodiments, the numerical parameters should be
`construed in light of the number of reported significant digits
`and by applying ordinary rounding techniques. Notwith-
`standing that the numerical ranges and parameters setting
`forth the broad scope of some embodiments of the invention
`are approximations, the numerical values set forth in the
`
`

`

`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 9 of 13 Page ID #:19
`Case 2:20-cv-11056-JVS—JPR Document 1-1 Filed 12/04/20 Page 9 of 13 Page ID #:19
`
`US 10,728,619 B2
`
`3
`specific examples are reported as precisely as practicable.
`The numerical values presented in some embodiments of the
`invention may contain certain errors necessarily resulting
`from the standard deviation found in their respective testing
`measurements.
`
`As used in the description herein and throughout the
`claims that follow, the meaning of “a,” “an,” and “the”
`includes plural reference unless the context clearly dictates
`otherwise. Also, as used in the description herein,
`the
`meaning of “in” includes “in” and “on” unless the context
`clearly dictates otherwise.
`Unless the context dictates the contrary, all ranges set
`forth herein should be interpreted as being inclusive of their
`endpoints, and open-ended ranges should be interpreted to
`include only commercially practical values. Similarly, all
`lists of values should be considered as inclusive of interme-
`
`diate values unless the context indicates the contrary.
`The recitation of ranges of values herein is merely
`intended to serve as a shorthand method of referring indi-
`vidually to each separate value falling within the range.
`Unless otherwise indicated herein, each individual value
`with a range is incorporated into the specification as if it
`were individually recited herein. All methods described
`herein can be performed in any suitable order unless other-
`wise indicated herein or otherwise clearly contradicted by
`context. The use of any and all examples, or exemplary
`language (e.g. “such as”) provided with respect to certain
`embodiments herein is intended merely to better illuminate
`the invention and does not pose a limitation on the scope of
`the invention otherwise claimed. No language in the speci-
`fication should be construed as indicating any non-claimed
`element essential to the practice of the invention.
`Groupings of alternative elements or embodiments of the
`invention disclosed herein are not to be construed as limi-
`
`tations. Each group member can be referred to and claimed
`individually or in any combination with other members of
`the group or other elements found herein. One or more
`members of a group can be included in, or deleted from, a
`group for reasons of convenience and/or patentability. When
`any such inclusion or deletion occurs, the specification is
`herein deemed to contain the group as modified thus fulfill-
`ing the written description of all Markush groups used in the
`appended claims.
`The
`following discussion provides many example
`embodiments of the inventive subject matter. Although each
`embodiment represents a single combination of inventive
`elements,
`the inventive subject matter is considered to
`include all possible combinations of the disclosed elements.
`Thus if one embodiment comprises elements A, B, and C,
`and a second embodiment comprises elements B and D, then
`the inventive subject matter is also considered to include
`other remaining combinations of A, B, C, or D, even if not
`explicitly disclosed.
`As used herein, and unless the context dictates otherwise,
`the term “coupled to” is intended to include both direct
`coupling (in which two elements that are coupled to each
`other contact each other) and indirect coupling (in which at
`least one additional element is located between the two
`
`elements). Therefore, the terms “coupled to” and “coupled
`wit ” are used synonymously.
`FIG. 1 is a functional block diagram illustrative a distrib-
`uted data processing environment.
`As used herein, the term “distributed” describes a com-
`puter system that
`includes multiple, physically distinct
`devices that operate together as a single computer system.
`FIG. 1 provides only an illustration of one implementation
`and does not
`imply any limitations with regard to the
`
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`environments in which different embodiments may be
`implemented. Many modifications to the depicted environ-
`ment may be made by those skilled in the art without
`departing from the scope of the invention as recited by the
`claims.
`
`Distributed data processing environment 100 includes
`user device 104 and server computer 108, interconnected
`over network 102. Network 102 can include, for example, a
`telecommunications network, a local area network (LAN), a
`wide area network (WAN), such as the Internet, or a com-
`bination of the three, and can include wired, wireless, or
`fiber optic connections. Network 102 can include one or
`more wired and/or wireless networks that are capable of
`receiving and transmitting data, voice, and/or video signals,
`including multimedia signals that include voice, data, and
`video information. In general, network 102 can be any
`combination of connections and protocols that will support
`communications between user device 104, server computer
`108, and any other computing devices (not shown) within
`distributed data processing environment 100.
`It
`is contemplated that user device 104 can be any
`programmable electronic computing device capable of com-
`municating with various components and devices within
`distributed data processing environment 100, via network
`102. It is further contemplated that user device 104 can
`execute machine readable program instructions and com-
`municate with any devices capable of communication wire-
`lessly and/or through a wired connection. For example, user
`device 104 can be any one or more of smart phones, desktop
`computers, tablet computers, laptops, and smart watches. It
`is contemplated that user device 104 also includes any one
`or more communicatively coupled peripheral electronic
`devices (e.g., computer mice, keyboards, electronic sensors,
`communication devices, storage devices, etc.). User device
`104 includes an instance of ad interface 106.
`
`Ad interface 106 provides a user interface to ad engine
`110. Preferably, ad interface 106 comprises a graphical user
`interface (GUI) or a web user interface (WUI) that can
`display one or more of text, documents, web browser
`windows, user option, application interfaces, and opera-
`tional instructions. It is also contemplated that the ad inter-
`face can include information, such as, for example, graphics,
`texts, and sounds that a program presents to a user and the
`control sequences that allow a user to control a program.
`In some embodiments, user interface can be mobile
`application software. Mobile application software, or an
`“app,” is a computer program designed to run on smart
`phones, tablet computers, and any other mobile devices.
`Ad interface 106 allows a user to register with and
`configure ad engine 110 (discussed in more detail below) to
`enable ad engine 110 to track user activity and preferences
`and respond to user media playback actions. It is contem-
`plated that ad interface 106 allows a user to provide any
`information to ad engine 110. For example, a user can input
`authentication,
`advertisement parameters, product pur-
`chases, user information, and any other information that is
`used by ad engine 110. As used herein, “advertisement
`parameters” comprise any variable(s) that can directly or
`indirectly control how ad engine 110 executes advertise-
`ments and receives user inputs.
`Ad interface 106 is also contemplated to allow a user to
`complete any type of transaction. For example, ad interface
`106 can receive user payment data and execute a financial
`transaction. In another example, ad interface 106 can receive
`user credentials to log-in to third-party services.
`Server computer 108 can be a standalone computing
`device, a management server, a web server, a mobile com-
`
`

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`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 10 of 13 Page ID #:20
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 10 of 13 Page ID #:20
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`US 10,728,619 B2
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`puting device, or any other computing system capable of
`receiving, sending, and processing data.
`It is contemplated that server computer 108 can include a
`server computing system that utilizes multiple computers as
`a server system, such as, for example, a cloud computing
`system.
`In other embodiments, server computer 108 can be a
`computer system utilizing clustered computers and compo-
`nents that act as a single pool of seamless resources when
`accessed within distributed data processing environment
`100.
`
`Ad engine 110 is depicted and described in more detail in
`FIG. 2, FIG. 3, and FIG. 4.
`Database 112 is a repository for data used by ad engine
`110. In the depicted embodiment, ad engine 110 resides on
`server computer 108. However, database 112 can reside
`anywhere within a distributed data processing environment
`provided that ad engine 110 has access to database 112.
`Data storage can be implemented with any type of data
`storage device capable of storing data and configuration files
`that can be accessed and utilized by server computer 108.
`Data storage devices can include, but are not limited to,
`database servers, hard disk drives, flash memory, and any
`combination thereof.
`
`FIG. 2 is a schematic of a method of using user data to
`determine an advertisement policy for a user.
`Ad engine 110 identifies a user (step 202).
`In one embodiment, ad engine 110 identifies a user based
`on a user credential inputted through ad interface 106. User
`credentials can include any one or more identifying attri-
`butes of a user.
`
`For example, ad engine 110 can identify a user through a
`user name and associated alphanumeric password inputted
`through log-in process on an internet-connected smart TV. In
`another example, ad engine 110 can identify a user through
`an internet protocol (IP) address tied to a desktop computer.
`In yet another example, ad engine 110 can identify a user
`through biometric data inputted through a fingerprint reader
`on a laptop.
`Biometric data can include, but is not limited to, finger-
`prints, retinal scans, image recognition, facial recognition,
`and speech recognition. It is also contemplated that user
`device 104 can collect biometric data using any combination
`of sensors. Sensors can include, but are not limited to,
`infrared cameras,
`flood illuminators, proximity sensors,
`ambient light sensors, capacitive touch sensors, pressure-
`based touch sensors, and microphones.
`In a related embodiment, ad engine 110 can use a com-
`bination of user credentials to identify a user. For example,
`ad engine 110 can use a combination of a facial recognition
`scan and an IP address to identify the user. In another
`example, ad engine 110 can use a combination of a pin
`number and a fingerprint scan to identify the user.
`However,
`it
`is contemplated that ad engine 110 can
`identify a user in any manner contemplated in the art.
`Ad engine 110 receives user data (step 204).
`It is contemplated that user data can be retrieved from
`local storage and/or remote storage. User data can include
`any data associated with a user,
`including, for example,
`purchasing behavior, media consumption behavior, media
`content data, geolocation data, and biometric data.
`In one embodiment, ad engine 110 receives user data from
`database 112 residing remotely on server computer 108. For
`example, ad engine 110 can receive data regarding a user’s
`viewing habits, shows watched, purchase history, and recent
`keyword searches from a solid-state drive (SSD) residing in
`a remote server through the Internet. In another example, ad
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`engine 110 can receive data regarding a user’s viewing
`habits from multiple databases in a distributed database
`system in a cloud environment.
`Ad engine 110 determines an advertisement policy for the
`user based on the user data (step 206).
`An advertisement policy can comprise any one or more
`parameters that guide ad engine 110 in the selection of
`advertisements for a user.
`
`In one embodiment, ad engine 110 determines an adver-
`tisement policy for a user using one or more metrics asso-
`ciated with the user data. For example, ad engine 110 can use
`data regarding user screen time, most watched genres, and
`commonly purchased products/services to set parameters for
`advertisement selection. It is contemplated that the param-
`eters can be set by one or more algorithms.
`In some embodiments, ad engine 110 can determine an
`advertisement policy for a user using one or more machine
`learning algorithms. Machine learning algorithms can
`include, but are not limited to, linear regression analysis,
`supervised learning, time-series analysis, and neural net-
`works.
`
`For example, ad engine 110 can use a supervised learning
`classifier to identify that the user frequently watches ani-
`mated content directed to a mid-20-year-old demographic.
`Ad engine 110 can further use a time-series analysis to
`determine that the user consumes the most content between
`the hours of 7:00 A.M-8:00 AM. and 6:00 P.M.-10:00 PM.
`
`Ad engine 110 can even further use a linear regression
`analysis to forecast that the user is four times more likely to
`purchase products during the hours of 8:00 P.M.-9:30 P.M.
`Based on this information, ad engine 110 can determine a
`tailored advertisement policy for the user.
`Ad engine 110 applies the advertisement policy for the
`user to available advertisements to select one or more
`
`advertisements (step 208).
`It
`is contemplated that advertisements in any media
`format can be stored locally and/or remotely. It is further
`contemplated that ad engine 110 can classify the advertise-
`ment in any manner contemplated in the art. For example, an
`advertisement for a male body spray can be can be classified
`under “30 second ad”, “20-30 years old”, “quirky humor”,
`and “interactive”. In another example, an advertisement for
`a high-end laptop computer can be classified under “expen-
`sive”, “technology”, and “designer”.
`Using these classifications, ad engine 110 can quickly
`target and retrieve relevant advertisements based on user
`viewing behaviors. For example, ad engine 110 can quickly
`select advertisements most relevant to a 23-year-old video
`game enthusiast by searching for ads under the classifica-
`tions “gamer”, “massively multiplayer online role-playing
`game”, “alcohol”, and “animated”.
`Similarly to step 206, ad engine 110 can use one or more
`machine learning algorithms to classify advertisements and
`to select one or more relevant advertisements. For example,
`ad engine 110 can use a supervised learning classifier to
`determine what type of advertisement content receives the
`most clicks and/or purchase orders from a user. By analyzing
`the historically successful ads, ad engine 110 can determine
`which advertisements contain content that is the most likely
`to elicit a click and/or purchase order from the user.
`Ad engine 110 compiles user relevant advertisements
`based on the advertisement policy (step 210).
`After applying the advertisement policy to select one or
`more advertisements, ad engine 110 compiles the advertise-
`ments for later playback. In some embodiments, ad engine
`110 retrieves advertisement data (e.g., audio and video files,
`etc.) and stored the advertisement data in local memory for
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`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 11 of 13 Page ID #:21
`Case 2:20-cv-11056-JVS-JPR Document 1-1 Filed 12/04/20 Page 11 of 13 Page ID #:21
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`US 10,728,619 B2
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`later playback. For example, ad engine 110 can cause user
`device 104 to pre-load advertisement content into random
`access memory (RAM) for later playback during a user-
`initiated pause.
`FIG. 3 is a schematic of a method of compiling and
`initiating playback of advertisements in response to a media
`playback action.
`Ad engine 110 detects user initiation of media playback
`(step 302).
`In one embodiment, ad engine 110 detects the selection of
`a media file for playback. For example, ad engine 110 can
`detect the selection of a television comedy from an over-
`the-top media streaming service. In another example, ad
`engine 110 can detect a user resuming playback of paused
`content.
`
`In some embodiments, ad engine 110 detects user actions
`prior to initiation of media playback. For example, ad engine
`110 can detect a video streaming device waking up from a
`sleep mode and detect which shows the user scrolls over
`prior to making a final selection.
`It
`is contemplated that detecting user actions prior to
`initiation of media playback enables ad engine 110 to
`analyze and predict the type of media content that the user
`will eventually select. For example, ad engine 110 can detect
`that a user has scrolled over and read the synopsis of three
`romantic comedies. Based on detected user behavior, ad
`engine 110 can predict one or more media attributes of the
`final selection, which can, for example, allow ad engine 110
`to start compiling relevant advertisements.
`Ad engine 110 retrieves the advertisement policy (step
`304).
`In a preferred embodiment, ad engine 110 retrieves the
`advertisement policy from database 112 stored remotely in
`server computer 108. However, ad engine 110 can retrieve
`the advertisement policy from any one or more storage
`mediums. For example, ad engine 110 can retrieve the
`advertisement policy from a distributed database system
`(e.g., cloud storage).
`Ad engine 110 analyzes media attributes to filter one or
`more advertisements from available advertisements (step
`306).
`Media attributes include any objective and subjective
`characteristics of the media content itself. Objective char-
`acteristics can include, for example, total playback time,
`listed actors/actresses, total number of episodes, and genres.
`Subjective characteristics can include, for example, type of
`humor, tone, and pacing. However, the objective and sub-
`jective characteristics listed herein are merely illustrative
`and are not limited to the provided examples.
`It is contemplated that ad engine 110 can use apply the
`advertisement policy to the analyzed media attributes to
`assist in determining which advertisements to run. In pre-
`ferred embodiments, ad engine 110 uses the analyzed media
`attributes to select advertisements. For example, ad engine
`110 can determine that a user selected video spans 2 hours
`and is associated with the horror genre. Based on this
`information, ad engine 110 can select advertisements with
`darker color tones, set advertisements to run every 15
`minutes, and set advertisement breaks to a length of 4
`minutes per break.
`Ad engine 110 queues advertisements based on the ana-
`lyzed media attributes and the advertisement policy (step
`308).
`It is contemplated that ad engine 110 queues advertise-
`ments that are the most relevant to the user by applying the
`user-specific advertisement policy to the filtered advertise-
`ments based on analyzed media attributes.
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