AI Personalization for User-Graph Content Authoring

Solution Overview

Problem

Conventional AI-driven summarization technologies are limited to extracting string-based summaries and are ineffective for content that has not been recently accessed, requiring manual input and resource-intensive searches across multiple sources.

Innovation Solution

An AI personalization application that generates contextual data by analyzing user graphs, identifying relevant nodes and edges, and incorporating this data into content authoring applications, reducing the need for manual input and multiple searches.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If conventional AI-driven summarization is used to extract string-based summaries, then summarization of recently accessed content is possible, but it cannot summarize content that has not been recently accessed and requires manual input

Engineering Contradiction:

Improveautomation of content summarizationVSAvoidability to summarize any content regardless of access time

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The system performs preliminary actions by proactively searching for and summarizing content from multiple sources before the user actually needs it. When a user creates or edits content, the system has already gathered relevant information, references, and context from emails, documents, spreadsheets, and other sources, making the summarization process seamless and eliminating the need for manual content gathering.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically performing content gathering, searching, and summarization without requiring manual user input. The AI assistant autonomously identifies relevant content across different applications and sources, extracts key information, and integrates it into the user's content, allowing the system to serve itself in completing the content creation task.

Inventive Principle:

Principle #25Self-service

2Productivity

If manual input is required to search for and copy information from multiple sources, then content can be assembled, but the process becomes frustrating and time-consuming

Engineering Contradiction:

Improvecontent creation speedVSAvoiduser effort required for content assembly

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The system enables self-service by automatically performing content gathering, searching, and summarization without requiring manual user input. The AI assistant autonomously identifies relevant content across different applications and sources, extracts key information, and integrates it into the user's content, allowing the system to serve itself in completing the content creation task.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process of searching, copying, and pasting information with an AI-driven automated system. Instead of the user manually navigating through emails, documents, and spreadsheets to find and copy relevant information, the AI assistant performs these operations automatically, substituting the mechanical user actions with intelligent automation that is both faster and more efficient.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Loss of information

If the computing device receives manual input to search multiple sources, then information can be located, but processing search queries becomes burdensome on computing resources

Engineering Contradiction:

Improvecompleteness of information gatheringVSAvoidcomputing resource consumption

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary actions by proactively searching for and summarizing content from multiple sources before the user actually needs it. When a user creates or edits content, the system has already gathered relevant information, references, and context from emails, documents, spreadsheets, and other sources, making the summarization process seamless and eliminating the need for manual content gathering.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12443669B2Artificial intelligence driven personalization for content authoring applications

Publication Date: 2025.10.14 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A computing system obtain a keyword and an identifier for a user of a content authoring application. Based upon the keyword and identifier for the user, the computing system walks a user graph comprising nodes connected by edges. The walk comprises identifying seed nodes in the user graph representing at least one topic that corresponds to the keyword and identifying second level nodes in the user graph that are connected to the seed nodes. The second level nodes represent first content that is associated with the user. The computing system transmits contextual data that is based upon the first content to the content authoring application. The contextual data is processed and formatted and is included in second content presentable by the content authoring application. The contextual data may be used to autogenerate the second content without user input. The second content may be modified by the user as desired.