Method and system for literacy adaptive content personalization

Patent metadata

Field	Value
Publication number	US-12461978-B2
Application number	US-202218061625-A
Country	US
Kind code	B2
Filing date	Dec 5, 2022
Priority date	Dec 24, 2019
Publication date	Nov 4, 2025
Grant date	Nov 4, 2025

Abstract

The present teaching relates to a method, system, and programming for content personalization. A request is received from a user to obtain a content item. Information indicative of a literacy-level of the user is obtained and the content item to be provided to the user is retrieved. The content item is modified by updating information included in the content item based on the literacy-level of the user to generate an updated content item. The updated content item is provided to the user in response to the request.

First claim

We claim:

1 . A method for content personalization, the method comprising:
retrieving, by a content modification engine, content items previously consumed by a first user; retrieving, from a database based on metadata of a request from the first user, a first literacy score of the first user; determining a social group including the first user and other users, wherein the other users have also consumed the content items; refining, based on literacy scores of the other users and an average literacy score of content items composed by the first user, the first literacy score of the first user, wherein the average literacy score is determined based on a readability score of each of the content items composed by the first user; modifying, in accordance with a model and based on the refined first literacy score of the first user, a first content item identified based on a request from the first user to generate multiple versions of the first content item, wherein at least some of text of each of the multiple versions is replaced by replacement text; verifying each of the multiple versions of the first content item based on a difference between the refined first literacy score of the first user and a literacy score of the version; and providing, in response to the request, at least one of the verified versions of the first content item to the first user by using a graphical model to embed a pop-up box including a description of the replacement text.

2 . The method of claim 1 , wherein the refining the first literacy score is to either increase or decrease the first literacy score.

3 . The method of claim 1 , further comprising computing an average literacy score of the literacy scores of the other users.

4 . The method of claim 3 , wherein the refining the first literacy score is based on the average literacy score.

5 . The method of claim 1 , further comprising:
generating multiple versions of the first content item by updating information included in the first content item based on a granularity level; and selecting one of the multiple versions to correspond to the updated first content item to be provided to the user.

6 . The method of claim 1 , further comprising storing the refined first literacy score in a database.

7 . A non-transitory, computer-readable medium having information recorded thereon for content personalization, wherein the information, when read by at least one processor, effectuates operations comprising:
retrieving, by a content modification engine, content items previously consumed by a first user; retrieving, from a database based on metadata of a request from the first user, a first literacy score of the first user; determining a social group including the first user and other users, wherein the other users have also consumed the content items; refining, based on literacy scores of the other users and an average literacy score of content items composed by the first user, the first literacy score of the first user, wherein the average literacy score is determined based on a readability score of each of the content items composed by the first user; modifying, in accordance with a model and based on the refined first literacy score of the first user, a first content item identified based on a request from the first user to generate multiple versions of the first content item, wherein at least some of text of each of the multiple versions is replaced by replacement text; verifying each of the multiple versions of the first content item based on a difference between the refined first literacy score of the first user and a literacy score of the version; and providing, in response to the request, at least one of the verified versions of the first content item to the first user by using a graphical model to embed a pop-up box including a description of the replacement text.

8 . The medium of claim 7 , wherein the refining the first literacy score is to either increase or decrease the first literacy score.

9 . The medium of claim 7 , wherein the operations further comprise computing an average literacy score of the literacy scores of the other users.

10 . The medium of claim 9 , wherein the refining the first literacy score is based on the average literacy score.

11 . The medium of claim 7 , wherein the operations further comprise:
generating multiple versions of the first content item by updating information included in the first content item based on a granularity level; and selecting one of the multiple versions to correspond to the updated first content item to be provided to the user.

12 . The medium of claim 7 , wherein the operations further comprise storing the refined first literacy score in a database.

13 . A system for content personalization, the system comprising:
memory storing computer program instructions; and one or more processors that, in response to executing the computer program instructions, effectuate operations comprising: retrieving, by a content modification engine, content items previously consumed by a first user; retrieving, from a database based on metadata of a request from the first user, a first literacy score of the first user; determining a social group including the first user and other users, wherein the other users have also consumed the content items; refining, based on literacy scores of the other users and an average literacy score of content items composed by the first user, the first literacy score of the first user, wherein the average literacy score is determined based on a readability score of each of the content items composed by the first user; modifying, in accordance with a model and based on the refined first literacy score of the first user, a first content item identified based on a request from the first user to generate multiple versions of the first content item, wherein at least some of text of each of the multiple versions is replaced by replacement text; verifying each of the multiple versions of the first content item based on a difference between the refined first literacy score of the first user and a literacy score of the version; and providing, in response to the request, at least one of the verified versions of the first content item to the first user by using a graphical model to embed a pop-up box including a description of the replacement text.

14 . The system of claim 13 , wherein the refining the first literacy score is to either increase or decrease the first literacy score.

15 . The system of claim 13 , wherein the operations further comprise computing an average literacy score of the literacy scores of the other users.

16 . The system of claim 15 , wherein the refining the first literacy score is based on the average literacy score.

17 . The system of claim 13 , wherein the operations further comprise:
generating multiple versions of the first content item by updating information included in the first content item based on a granularity level; and selecting one of the multiple versions to correspond to the updated first content item to be provided to the user.

Assignees

• Yahoo Assets Llc

Inventors

• Pelleg Dan
• Wolff Ran
• Mejer Avihai

Classifications

• G06F16/9538 Primary

  Presentation of query results · CPC title

• G06F16/219

  Managing data history or versioning (querying versioned data G06F16/2474; querying temporal data G06F16/2477) · CPC title

• G06F16/9535 Primary

  Search customisation based on user profiles and personalisation · CPC title