Microsoft Technology Licensing, LLC

Jennifer Rose Guriel

Gershom L Payzer

Christopher Ian Charla

Bridgette Marie Kuehn

Madeline Jaye Whisenant

Kathryn Stone Perez

Mingqi Wu

Lily Wang

Licheng Pan

Abdelrahman Khaled Abdo Mohamed

Jianxun Lian

This disclosure relates to a content cluster system that provides a framework for leveraging large language models (LLMs) to tag content items (e.g., interactive multimedia content items, such as gaming content items) with attribute tags and, based on attribute tags for related content items, generating cluster descriptions of a cluster of content items. Features of the content cluster system involve tagging content items, determining multi-dimensional embeddings for the content items, and clustering the content items based on proximity of values contained within the multi-dimensional embeddings. The content cluster system may further utilize the LLM to generate one or more cluster descriptions based on the associated tags to create a more creative and dynamic representation of related groupings of titles (e.g., gaming titles). By utilizing LLMs and machine learning resources, the content cluster system provides a scalable approach to conventional approaches in determining and presenting groupings of titles.

Systems and methods for clustering digital content

A method of recommending an unplayed game application to a user includes obtaining a game history associated with a user profile, wherein the game history includes at least one game record of a game application the user profile has been used to play, and evaluating the game history to obtain a plurality of game events associated with a game application of the game history. The method further includes accessing a table of tags associated with the plurality of game events associated with the game application, aggregating a plurality of tags in a tag list in the user profile based at least partially on the table of tags and the plurality of game events, and presenting to the user a recommendation of an unplayed game application based at least partially on the plurality of tags.

Systems and methods for rich personalization of computer game experiences

Growing community of inventors

Bothell, WA, United States of America

Jennifer Rose Guriel