Google llc (20240232945). MACHINE LEARNING-BASED AUTOMATED TARGETING EXPANSION SYSTEM simplified abstract
Contents
MACHINE LEARNING-BASED AUTOMATED TARGETING EXPANSION SYSTEM
Organization Name
Inventor(s)
Bharath Pattabiraman of Santa Clara CA (US)
MACHINE LEARNING-BASED AUTOMATED TARGETING EXPANSION SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240232945 titled 'MACHINE LEARNING-BASED AUTOMATED TARGETING EXPANSION SYSTEM
The abstract describes systems and methods for assessing the relevancy of search queries using machine learning techniques. The computing device determines if a search query can display content, assigns a category to the query, and identifies a relevant content item. It also analyzes additional queries with a relaxed threshold to assess relevancy and updates the machine learning model with engagement data.
- Computing device uses machine learning techniques to assess search query relevancy
- Determines if a search query can display content and assigns a category
- Identifies a relevant content item associated with the category
- Analyzes additional queries with a relaxed threshold to assess relevancy
- Updates machine learning model with engagement data
Potential Applications: - Search engine optimization - Content recommendation systems - E-commerce product recommendations
Problems Solved: - Improving search query relevancy - Enhancing user engagement with content - Optimizing content display based on user queries
Benefits: - Increased user satisfaction - Higher click-through rates - Improved content relevance
Commercial Applications: Title: Enhanced Search Query Relevancy System This technology can be used in search engines, e-commerce platforms, and content recommendation systems to improve user experience and drive engagement. It has the potential to increase conversion rates and revenue for businesses by delivering more relevant content to users.
Questions about the technology: 1. How does this technology improve user engagement with search queries? 2. What are the potential implications of using machine learning in search query relevancy assessment?
Original Abstract Submitted
systems and methods for assessing the relevancy of search queries are described. a computing device uses various machine learning techniques to determine whether a search query presents an opportunity to display content as well as determine a category for the search query and a content item associated with the category. the computing device additional analyzes an additional search query using a machine learning model with a relaxed threshold to assess relevancy. the computing device captures engagement data associated with a user engaging with the content item and update the machine learning model with the engagement data.
