Spotify ab (20240346079). SYSTEMS AND METHODS FOR GENERATING SYNTHETIC QUERIES simplified abstract
Contents
SYSTEMS AND METHODS FOR GENERATING SYNTHETIC QUERIES
Organization Name
Inventor(s)
Gustavo Penha of Amsterdam (NL)
Maryam Aziz of Princeton Juction NJ (US)
Alice Wang of New York NY (US)
Hugues Bouchard of Barcelona (ES)
SYSTEMS AND METHODS FOR GENERATING SYNTHETIC QUERIES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346079 titled 'SYSTEMS AND METHODS FOR GENERATING SYNTHETIC QUERIES
Simplified Explanation: The patent application describes an electronic device that generates synthetic queries based on specific parameters for media content items, displays these queries to users, and provides corresponding result sets of media content items.
Key Features and Innovation:
- Electronic device generates synthetic queries for media content items.
- Queries are based on specific parameters indicating query specificity.
- Users select queries displayed on client devices.
- Device provides result sets of media content items based on user-selected queries.
Potential Applications: This technology can be applied in search engines, content recommendation systems, and personalized advertising platforms.
Problems Solved: This technology addresses the challenge of generating relevant and specific queries for media content items to improve user experience and search accuracy.
Benefits:
- Enhanced user experience with tailored queries.
- Improved search accuracy and relevance of search results.
- Increased user engagement with media content items.
Commercial Applications: Potential commercial applications include search engine optimization tools, content recommendation services, and targeted advertising platforms for businesses.
Prior Art: Prior art related to this technology may include research on query generation algorithms, personalized search systems, and content recommendation techniques.
Frequently Updated Research: Researchers may be exploring advancements in query generation algorithms, user behavior analysis for query specificity, and machine learning models for personalized content recommendations.
Questions about the Technology: 1. How does this technology improve user engagement with media content items? 2. What are the key parameters used to generate synthetic queries for media content items?
Original Abstract Submitted
an electronic device provides, to a model trained to generate synthetic queries, information corresponding to a first media content item and a first value for a parameter indicative of query specificity. the device receives, from the model trained to generate synthetic queries, a first query corresponding to the first media content item, wherein the first query is generated in accordance with the first value for the parameter indicative of query specificity. the device provides, to a client device for display at the client device, the first query and receives user selection of the first query. in response to the user selection of the first query, the device provides a first result set of media content items for the first query.
