Microsoft technology licensing, llc (20240184836). PERSONALIZED RETRIEVAL simplified abstract

PERSONALIZED RETRIEVAL

Organization Name

microsoft technology licensing, llc

Inventor(s)

Shivam Mittal of New Dehli (IN)

Sheshansh Agrawal of Bellevue WA (US)

Hemanth Vemuri of Hyderabad (IN)

Deepak Saini of Bellevue WA (US)

Akshay Soni of Santa Clara CA (US)

Abhinav Viswanathan Sambasivan of Milpitas CA (US)

Yajun Wang of Sunnyvale CA (US)

Mehulkumar Parsana of Bellevue WA (US)

Wenhao Lu of Seattle WA (US)

Manik Varma of South Moti Bagh (IN)

PERSONALIZED RETRIEVAL - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240184836 titled 'PERSONALIZED RETRIEVAL

Simplified Explanation

The patent application describes systems and methods for personalized retrievals of items by creating a user-specific morph operator to capture user preferences and transform generic queries into personalized ones.

• User-specific morph operator captures learned user preferences.
• Transforms generic query embeddings into personalized ones.
• Retrieves items based on user preferences for the query.

Key Features and Innovation

• Creation of user-specific morph operator.
• Transformation of generic query embeddings into personalized ones.
• Retrieval of items based on user preferences.

Potential Applications

The technology can be applied in personalized recommendation systems, e-commerce platforms, personalized search engines, and content curation services.

Problems Solved

The technology addresses the challenge of providing personalized recommendations and search results based on user preferences.

Benefits

• Enhanced user experience with personalized recommendations.
• Improved relevance of search results.
• Increased user engagement and satisfaction.

Commercial Applications

• Personalized recommendation systems for e-commerce platforms.
• Enhanced search engines for personalized results.
• Content curation services for tailored content delivery.

Prior Art

There is no specific information provided on prior art related to this technology.

Frequently Updated Research

There is no specific information provided on frequently updated research relevant to this technology.

Questions about Personalized Retrievals of Items

Question 1

How does the user-specific morph operator capture user preferences?

The user-specific morph operator captures user preferences by analyzing the user's interactions and behaviors to learn their preferences over time.

Question 2

What are the potential implications of using personalized embeddings for query retrieval?

Using personalized embeddings for query retrieval can lead to more accurate and relevant search results for users, enhancing their overall search experience.

Original Abstract Submitted

the present disclosure relates to systems and methods for providing personalized retrievals of items. the systems and methods create a user-specific morph operator for a user that captures learned user preferences for the user. the systems and methods use the user-specific morph operator to transform a generic embedding for a query into a personalized embedding for the query. the systems and method use the personalized embedding to retrieve items based on the user preferences to present in response to the query.