IP Library Granted Patent US 12,242,531
Granted Patent B2
US 12,242,531 · App. 18/214,719 · Granted Mar 4, 2025

Publisher tool for controlling sponsored content quality across mediation platforms

Inventors: Thomas Price (San Francisco, CA); Tuna Toksoz (Mountain View, CA)
Assignee: GOOGLE LLC
G06F16/583G06F16/958G06F18/24323G06Q30/0241G06V30/224
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,242,531
App. No.
18/214,719
Granted
Mar 4, 2025
Kind
B2
Abstract

Systems and methods are described for providing an interface and facilitating selection of sponsored content networks that provide sponsored content items. This may include providing, by a mediation server, a user interface to a publisher server, the user interface configured to provide access to data stored on the mediation server; receiving a metric associated with a rule for filtering content items associated with the publisher; applying the metric to a content network list associated with the publisher using the user interface to generate an updated content network list; and transmitting mediation code including the updated content network list to the publisher server, wherein the mediation code, when executed by a user device, (i) causes the user device to control display of content items according to the updated content network list and (ii) allows the user device to flag at least one content item for modifying the updated content network list.

Claims (48)

1. A method to facilitate mediation of content selection, comprising:

providing, by a mediation server comprising a memory and one or more processors, a user interface to a publisher server, the user interface configured to provide access to data stored on the mediation server;

receiving, by the mediation server, a metric associated with a rule for filtering content items associated with the publisher;

applying, by the mediation server, the metric to a content network list associated with the publisher using the user interface to generate an updated content network list;

transmitting, by the mediation server, mediation code including the updated content network list to the publisher server,

wherein the mediation code, when executed by a user device, (i) causes the user device to control display of content items according to the updated content network list, (ii) allows the user device to flag at least one content item for modifying the updated content network list, and (iii) allows the user device to capture an image of the at least one content item responsive to flagging the at least one content item;

receiving, by the mediation server, an image of a content item flagged by the user device, the image captured by the user device;

updating, by the mediation server, the updated content network list to remove a content network providing the content item flagged by the user device to generate a further updated content network list; and

transmitting, by the mediation server, updated mediation code including the further updated content network list to cause the user device to control display of content items according to the further updated content network list.

2. The method of claim 1 , wherein the rule for filtering content items is associated with at least one of: (i) flagging of items by users, (ii) categories of content items based on image analysis, (iii) undesirable elements in content items, (iv) categories of content networks, (v) revenue of content networks, (vi) click through rate of content networks, or (vii) conversion rate of content networks.

3. The method of claim 1 , wherein the data stored on the mediation server includes at least one of: (i) content item identifiers of displayed content, (ii) image data associated with displayed content, (iii) flagging data associated with content items, or (iv) statistics associated with flagged content items.

4. The method of claim 1 , wherein the transmitting the mediation code occurs responsive to the applying the metric to the content network list.

5. The method of claim 1 , wherein the transmitting the mediation code occurs periodically according to a predetermined schedule.

6. The method of claim 1 , wherein the user interface includes one or more elements for a user to generate and transmit the metric to the mediation server.

7. The method of claim 1 , further comprising:

analyzing the received image of the content item flagged by the user device; and

wherein the updating the updated content network list is based on the analyzing.

8. The method of claim 7 , wherein the analyzing the received image includes:

generating, using a neural network, extracted text based on the received image.

9. The method of claim 8 , further comprising:

categorizing the received image of the content item based on the extracted text to determine a content item category of the content item;

wherein the updating the updated content network list is based on the content item category.

10. The method of claim 9 , wherein the categorizing is according to a probabilistic semantic language model.

11. A system for facilitating mediation of content selection, comprising:

one or more processors of a mediation server; and

a memory of the mediation server that is operatively coupled to the one or more processors, wherein the memory stores instructions that, when executed by the one or more processors, cause the one or more processors to:

provide a user interface to a publisher server, the user interface configured to provide access to data stored on the mediation server;

receive a metric associated with a rule for filtering content items associated with the publisher;

apply the metric to a content network list associated with the publisher using the user interface to generate an updated content network list; and

transmit mediation code including the updated content network list to the publisher server,

wherein the mediation code, when executed by a user device, (i) causes the user device to control display of content items according to the updated content network list, (ii) allows the user device to flag at least one content item for modifying the updated content network list, and (iii) allows the user device to capture an image of the at least one content item responsive to flagging the at least one content item;

receive an image of a content item flagged by the user device, the image captured by the user device;

update the updated content network list to remove a content network providing the content item flagged by the user device to generate a further updated content network list; and

transmit updated mediation code including the further updated content network list to cause the user device to control display of content items according to the further updated content network list.

12. The system of claim 11 , wherein the rule for filtering content items is associated with at least one of: (i) flagging of items by users, (ii) categories of content items based on image analysis, (iii) undesirable elements in content items, (iv) categories of content networks, (v) revenue of content networks, (vi) click through rate of content networks, or (vii) conversion rate of content networks.

13. The system of claim 11 , wherein the data stored on the mediation server includes at least one of: (i) content item identifiers of displayed content, (ii) image data associated with displayed content, (iii) flagging data associated with content items, or (iv) statistics associated with flagged content items.

14. The system of claim 11 , wherein the transmitting the mediation code occurs responsive to the applying the metric to the content network list.

15. The system of claim 11 , wherein the transmitting the mediation code occurs periodically according to a predetermined schedule.

16. The system of claim 11 , wherein the user interface includes one or more elements for a user to generate and transmit the metric to the mediation server.

17. The system of claim 11 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to:

analyze the received image of the content item flagged by the user device to generate an analysis of the received image; and

wherein updating the updated content network list is based on the analysis.

18. The system of claim 17 , wherein analyzing the received image includes:

generating, using a neural network, extracted text based on the received image.

19. The system of claim 18 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to:

categorize the received image of the content item based on the extracted text to determine a content item category of the content item;

wherein the updating the updated content network list is based on the content item category.

20. The system of claim 18 , wherein the categorizing is according to a probabilistic semantic language model.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 18, 2023
From: PRICE, THOMAS; TOKSOZ, TUNA
To: GOOGLE INC.
Reel/Frame 064636/0737 →
CHANGE OF NAME Recorded Aug 18, 2023
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 064646/0541 →
Continuity (3)
Continuation 16785317 · Feb 7, 2020
Continuation 15060339 · Mar 3, 2016
Related Publication 20230342391A1 · Oct 26, 2023
References Cited (36)
US 7971137B2 · Jindal et al. · 2011 [cited by applicant]
US 8311889B1 · Lagle Ruiz et al. · 2012 [cited by applicant]
US 8406739B2 · Hull et al. · 2013 [cited by applicant]
US 8472728B1 · Chau et al. · 2013 [cited by applicant]
US 20070038351A1 · Larschan et al. · 2007 [cited by applicant]
US 20070256033A1 · Hiler · 2007 [cited by examiner]
US 20090165140A1 · Robinson · 2009 [cited by examiner]
US 20100124907A1 · Hull · 2010 [cited by examiner]
US 20100145762A1 · Coladonato · 2010 [cited by examiner]
US 20100153548A1 · Wang · 2010 [cited by examiner]
US 20100332313A1 · Miller et al. · 2010 [cited by applicant]
US 20120158525A1 · Kae et al. · 2012 [cited by applicant]
US 20130024268A1 · Manickavelu · 2013 [cited by applicant]
US 20150178786A1 · Claessens · 2015 [cited by applicant]
US 20160234624A1 · Riva · 2016 [cited by examiner]
US 20170193545A1 · Zhou · 2017 [cited by examiner]
CN 101515282A · 2009 [cited by applicant]
CN 104823212A · 2015 [cited by applicant]
CN 104956360A · 2015 [cited by applicant]
WO WO2011014857A1 · 2011 [cited by applicant]
Grace et al: Unsafe exposure analysis of mobile in-app advertisements. In Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks (WISEC '12). Association for Computing Machinery,… [cited by examiner]
Ad Mob Ad Review Center: https://web.archive.org/webr/https://support.google.conn/adnnob/answer/3480906?h1=en&ref topic, attached. (Year: 2015). [cited by applicant]
“Selenium Training Expert” https://seleniunnonlinetrainingexpert.wordpress.conn/2012/11/29/how-to-capturing-screenshots-from-selenium-ide/ , attached (Year: 2012). [cited by applicant]
Son et al., “What Mobile Ads Know About Mobile Users”, NDSS, pp. 1-14, 2016, Retrieved from the Internet at: <https://www.ndss-symposium.org/wp-content/uploads/2017/09/what-mobile-ads-know-about-mobile-users.pdf>. [cited by applicant]
Craig Kanalley, “YouTube Gives Users Ability to Flag Content That Promotes Terrorism”, Huffpost, Dec. 13, 2010. Retrieved from the Internet at: <https://www.huffpost.com/entry/youtube-terrorism-flag_n_796128>. [cited by applicant]
First Office Action for CN Appin. Ser. No. 201780004862.3 dated Mar. 2, 2021. [cited by applicant]
“AdMob Help: About the ad review center”, 2015, retrieved Aug. 11, 2018 from URL: https://web.archive.org/web.archive.org/we/20151023153644/https://support.google.com/admob/answer/3480906?hl=en&ref topic (4 pages). [cited by applicant]
“AdMob Help: About your AdMob Network report”, Oct. 1, 2015, XP55376480, retrieved May 29, 2017 from URL: https://web.archive.org/web/20151001184738/https://support/google.com/admob/answer/6158845?hl=en (3 pages). [cited by applicant]
“AdMob Help: Block ads by ad network”, Oct. 23, 2015, retrieved Aug. 22, 2018 from URL: https://web.archive.org/web/20151023154646/https://support.google.com/admob/answer/6067448 (2 pages). [cited by applicant]
International Preliminary Report on Patentability for PCT Appin. Ser. No. PCT/US2017/020517 dated Jun. 6, 2018 (13 pages). [cited by applicant]
International Search Report and Written Opinion for PCT Appin. Ser. No. PCT/US2017/020517 dated Jul. 6, 2017 (16 pages). [cited by applicant]
Maken, “Adwords, AdSense, AdMob & DoubleClick: Internet Monetization”, Aug. 31, 2014, XP55375870, Retrieved May 24, 2017 from URL: http://www.gametheory.polimi.it/uploads/4/1/4/6/41466579/furthereadings_-_advertising.pd… [cited by applicant]
Non-Final Office Action for U.S. Appl. No. 15/060,339 dated Aug. 28, 2018 (16 pages). [cited by applicant]
Notice of Allowance for U.S. Appl. No. 15/060,339 dated Jan. 15, 2020 (3 pages). [cited by applicant]
Notice of Allowance for U.S. Appl. No. 15/060,339 dated Oct. 18, 2019 (14 pages). [cited by applicant]
First Chinese Office Action for Application No. 2021111074704, dated Dec. 25, 2024. [cited by applicant]