Method and system for identifying electronic devices of genuine customers of organizations

1. A computer-implemented method for identifying, among user electronic devices, customer electronic devices associated with genuine customers of organizations, the method being executed by a server, the method comprising:

receiving, from a first user electronic device and by the server, a first review submission;

determining a first user ID associated with the first user electronic device;

determining a second user electronic device associated with the first user ID;

sending, to the first user electronic device, a first request to provide a first browsing history stored on the first user electronic device;

sending, to the second user electronic device, a second request to provide a second browsing history stored on the second user electronic device;

receiving, from the first user electronic device, the first browsing history;

receiving, from the second user electronic device, the second browsing history;

selecting, from the first browsing history and the second browsing history, a first uniform resource locator (URL) corresponding to the first review submission;

generating a first embedding corresponding to the first URL;

comparing, by the server, the first embedding with a template embedding of a plurality of template embeddings, the plurality of template embeddings having been retrieved from a genuity database;

in response to a difference between the first embedding and the template embedding being lower than an embedding difference threshold;

adding the first embedding to the genuity database,

determining a static portion and a dynamic portion of the first URL,

generating, based on the static portion, a pattern-based embedding corresponding to the first URL,

generating, based on the dynamic portion, a mask-based embedding corresponding to the first URL,

storing the pattern-based embedding and the mask-based embedding in the genuity database in association with the first URL, and

marking, by the server, all reviews associated with the first user ID, in a recommendation database, as having been provided by a genuine customer;

receiving, by the server and from a third user electronic device associated with a second user ID, a second review submission;

determining a second URL corresponding to the second review submission;

generating a second embedding corresponding to the second URL;

comparing, by the server, the second embedding with the template embedding; and

after determining that a difference between the second embedding and the template embedding is greater than the embedding difference threshold:

deleting, by the server and from the recommendation database, all reviews associated with the second user ID, and

storing, in a fraudulent user database, the second user ID.

2. The method of claim 1 , the method further comprising:

in response to the difference between the first embedding and the template embedding being lower than the embedding difference threshold:

marking the first user electronic device as associated with a first genuine customer of a first organization; and

causing displaying of the first review submission on displays of future customers' electronic devices.

3. The method of claim 1 , the method further comprising generating the genuity database by:

receiving, by the server, a plurality of template transaction confirmation page URLs of genuity confirmation pages of corresponding template organizations; and

for each template transaction confirmation page URL of the template transaction confirmation page URLs, generating a new template embedding and storing the new template embedding in the genuity database, the new template embedding being one of the plurality of template embeddings.

4. The method of claim 3 , wherein at least one of the genuity confirmation pages is an online purchase confirmation page indicative of completion of a purchase by a genuine customer.

5. The method of claim 1 , further comprising, in response to the difference between the first embedding and the template embedding being lower than the embedding difference threshold:

associating the first embedding with a template URL pattern.

6. The method of claim 1 , further comprising, in response to the difference between the first embedding and the template embedding being lower than the embedding difference threshold:

generating a first URL pattern for the first URL; and

adding the first URL pattern to the genuity database.

7. The method of claim 6 , wherein the generating the first URL pattern comprises identifying a first dynamic portion of the first URL and a first static portion of the first URL.

8. The method of claim 7 , wherein:

the generating the first URL pattern comprises identifying at least one mask of a first pattern dynamic portion of the first URL pattern and identifying a first pattern static portion of the first URL pattern.

9. The method of claim 1 , wherein the method further comprises:

receiving, from a fourth user electronic device by the server, a third URL;

generating a third embedding corresponding to the third URL;

comparing the third embedding with the first embedding; and

in response to a difference between the third embedding and the first embedding being lower than the embedding difference threshold:

adding the third embedding to the genuity database.

10. The method of claim 1 , wherein the difference between the first embedding and the template embedding being lower than the embedding difference threshold is indicative of the first URL and a template URL having at least a partially common URL pattern.

11. The method of claim 1 , wherein the generating the first embedding comprises applying a Word2Vector algorithm to the first URL.

12. The method of claim 2 further comprising, in response to the difference between the first embedding and the template embedding being lower than the embedding difference threshold, and prior to causing displaying of the first review submission:

sending a review request to the first user electronic device requesting to provide comments on the first organization, the review request being configured to be displayed on a display of the first user electronic device.

13. The method of claim 2 , wherein the first organization is at least one of an online store, a booking service, and a service provider.

14. A computer-implemented system for identifying, among user electronic devices, customer electronic devices associated with genuine customers of organizations, the system comprising:

a genuity database;

a recommendation database; and

a server configured to:

receive, from a first user electronic device and by the server, a first review submission;

determine a first user ID associated with the first user electronic device;

determine a second user electronic device associated with the first user ID;

send, to the first user electronic device, a first request to provide a first browsing history stored on the first user electronic device;

send, to the second user electronic device, a second request to provide a second browsing history stored on the second user electronic device;

receive, from the first user electronic device, the first browsing history;

receive, from the second user electronic device, the second browsing history;

select, from the first browsing history and the second browsing history, a first uniform resource locator (URL) corresponding to the first review submission;

generate a first embedding corresponding to the first URL;

compare the first embedding with a template embedding of a plurality of template embeddings, the plurality of template embeddings having been retrieved from a genuity database;

in response to a difference between the first embedding and the template embedding being lower than an embedding difference threshold:

add the first embedding to the genuity database,

determine a static portion and a dynamic portion of the first URL, generate, based on the static portion, a pattern-based embedding corresponding to the first URL,

generate, based on the dynamic portion, a mask-based embedding corresponding to the first URL,

store the pattern-based embedding and the mask-based embedding in the genuity database in association with the first URL, and

and

mark all reviews associated with the first user ID, in the recommendation database, as having been provided by a genuine customer;

receive, from a third user electronic device associated with a second user ID, a second review submission;

determine a second URL corresponding to the second review submission;

generate a second embedding corresponding to the second URL;

compare the second embedding with the template embedding; and

after determining that a difference between the second embedding and the template embedding is greater than the embedding difference threshold:

delete, from the recommendation database, all reviews associated with the second user ID, and

store, in a fraudulent user database, the second user ID.