International business machines corporation (20240095290). DEVICE USAGE MODEL FOR SEARCH ENGINE CONTENT simplified abstract
Contents
- 1 DEVICE USAGE MODEL FOR SEARCH ENGINE CONTENT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DEVICE USAGE MODEL FOR SEARCH ENGINE CONTENT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DEVICE USAGE MODEL FOR SEARCH ENGINE CONTENT
Organization Name
international business machines corporation
Inventor(s)
Zachary A. Silverstein of Georgetown TX (US)
Lisa Ann Cassidy of Dublin (IE)
Kelley Anders of East New Market MD (US)
DEVICE USAGE MODEL FOR SEARCH ENGINE CONTENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095290 titled 'DEVICE USAGE MODEL FOR SEARCH ENGINE CONTENT
Simplified Explanation
The abstract describes a computer-implemented method for filtering search engine results for a user by maintaining a filtration layer, building a user search interaction model, and filtering search results based on the user's profile and historic search results.
- The method involves maintaining a filtration layer that is opted into by both the search engine and the client device.
- A user search interaction model is built based on the user's profile and historic search results, utilizing topic analysis on user interactions with historic search results.
- The user search interaction model is used to filter search results for a particular user search query on the client device.
Potential Applications
This technology could be applied in search engines, e-commerce platforms, and online advertising to provide more personalized and relevant search results to users.
Problems Solved
This technology helps solve the problem of information overload by filtering search results based on a user's profile and interactions, leading to more relevant and useful results.
Benefits
The benefits of this technology include improved user experience, increased user engagement, and more effective search results tailored to individual users.
Potential Commercial Applications
Potential commercial applications of this technology include search engine optimization tools, personalized advertising platforms, and recommendation systems for online content.
Possible Prior Art
One possible prior art for this technology could be personalized search algorithms used by major search engines to provide tailored search results to users.
What are the specific steps involved in building the user search interaction model?
The specific steps involved in building the user search interaction model include maintaining a filtration layer, performing topic analysis on user interactions with historic search results, selecting relevant topics based on user interaction amounts, and filtering search results for a particular user search query.
How does this technology impact user privacy and data security?
This technology may raise concerns about user privacy and data security as it involves analyzing user interactions with search results to build a personalized search interaction model. It is essential to ensure that user data is handled securely and in compliance with privacy regulations to address these concerns.
Original Abstract Submitted
a computer-implemented method for filtering search engine results for a user is provided. the method includes maintaining a filtration layer that is opted into by a search engine and a client device. the method further includes building a user search interaction model, operatively coupled to the filtration layer, based on a user's profile and historic search results by performing a topic analysis on a user's interactions with the historic search results and selecting a subset of relevant topics based on respective amounts of user interaction. the user interaction includes interactions on a plurality of different devices. the method also includes filtering search results produced for a particular user search query on the client device using the user search interaction model and the filtration layer.
