The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 16, 2026

Filed:

Mar. 22, 2024
Applicant:

Integral Ad Science, Inc., New York, NY (US);

Inventors:

Vikram Gupta, Pune, IN;

Karishma Agarwal, Pune, IN;

Mahesh Nagargoje, Latur, IN;

Sharad Pawar, Ahmednagar, IN;

Vinay Gaykar, Pune, IN;

Assignee:

Integral Ad Science, Inc., New York, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/0241 (2023.01); G06Q 10/0635 (2023.01); G06Q 30/018 (2023.01); G06Q 30/0273 (2023.01);
U.S. Cl.
CPC ...
G06Q 30/0277 (2013.01); G06Q 10/0635 (2013.01); G06Q 30/0185 (2013.01); G06Q 30/0275 (2013.01);
Abstract

Methods, systems, and media for providing contextual information associated with webpages are provided. In some embodiments, the method comprises: receiving a plurality of risk tolerance values from a first advertiser; accessing a first webpage through a first universal resource locator (URL), wherein the first webpage contains at least one dynamic advertising region; determining, using a machine learning model, (i) that the first URL is a cybersquatting attempt of a second URL based on a comparison of a first domain name associated with the first URL and a second domain name associated with the second URL; (ii) a first plurality of sentiments associated with content items within the first webpage, a plurality of keywords associated with the first webpage, and a similarity score between the first plurality of sentiments and the plurality of keywords; and (iii) a plurality of sentiment risk scores, wherein a sentiment risk score for at least one sentiment in the first plurality of sentiment risk scores is based on searching an approval list using at least one of the first plurality of sentiments as a search query; based on determining that the first URL is the cybersquatting attempt of the second URL, modifying an aggregate risk score by a first value from the plurality of risk tolerance values; based on determining that the similarity score is below a similarity threshold, modifying the aggregate risk score by a second value from the plurality of risk tolerance values; based on the plurality of sentiment risk scores, modifying the aggregate risk score by a third value from the plurality of risk tolerance values; determining that the aggregate risk score is within a first range of predetermined values; and in response to determining that the aggregate risk score is within the first predetermined range of values, associating at least one of the first webpage or the first domain name associated with the first URL with an exclusion list associated with the first advertiser.


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