View source for 20240037170. VALUE-BASED ONLINE CONTENT SEARCH ENGINE simplified abstract (Time Economy LTD.)

=VALUE-BASED ONLINE CONTENT SEARCH ENGINE=


==Organization Name==

[[:Category:Time Economy LTD.|Time Economy LTD.]]


[[Category:Time Economy LTD.]]

==Inventor(s)==

[[:Category:Amir Peled of Odense (DK)|Amir Peled of Odense (DK)]][[Category:Amir Peled of Odense (DK)]]

==VALUE-BASED ONLINE CONTENT SEARCH ENGINE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240037170 titled 'VALUE-BASED ONLINE CONTENT SEARCH ENGINE

==Simplified Explanation==

The patent application describes a method for generating value-based consumable items using machine learning models. Here is a simplified explanation of the abstract:

* The method involves receiving benefit parameters from users, which are defined with respect to interest domains, using client devices.
* Using generative machine learning models, the method generates consumable items related to the interest domains.
* A quantified benefit value is computed for each generated consumable item.
* The method selects the generated consumable items based on the correspondence between the quantified benefit values and the benefit parameters.
* Finally, the client devices are instructed to present the selected consumable items for consumption by the users.

Potential applications of this technology:

* Personalized recommendations: The method can be used to generate personalized recommendations for users based on their specific benefit parameters and interests.
* E-commerce platforms: The technology can be applied to e-commerce platforms to generate value-based consumable items for users, increasing customer satisfaction and engagement.
* Content streaming services: By using the method, content streaming services can provide personalized recommendations to users, improving user experience and retention.

Problems solved by this technology:

* Information overload: The method helps users navigate through a vast amount of information by generating consumable items that align with their benefit parameters and interests.
* Lack of personalization: By using machine learning models, the method enables personalized recommendations, addressing the issue of generic and irrelevant suggestions.
* Decision-making difficulties: The generated consumable items assist users in making decisions by presenting them with options that have quantified benefit values based on their preferences.

Benefits of this technology:

* Enhanced user experience: Users receive personalized recommendations and consumable items that align with their interests, leading to a more satisfying and tailored experience.
* Increased engagement: By presenting users with relevant and valuable consumable items, the technology can increase user engagement and interaction with the platform or service.
* Improved decision-making: The quantified benefit values assigned to the consumable items help users make informed decisions based on their preferences and priorities.


==Original Abstract Submitted==

a method of generating value based consumable items, comprising receiving one or more of a plurality of benefit parameters defined with respect to one or more of a plurality of interest domains selected by one or more users using respective client devices, generating one or more generated consumable items relating to the one or more interest domains using one or more generative machine learning (ml) models, computing a quantified benefit value for each of the plurality of generated consumable items, selecting one or more of the generated consumable items according to a correspondence between the quantified benefit value(s) of the respective generated consumable item and the one or more benefit parameters, and instructing one or more of client devices to present the selected one or more generated consumable items for consumption by one or more of the users.



[[Category:G06F16/957]]
[[Category:G06F16/9538]]
[[Category:G06F9/451]]