Expert Notification via Collaboration Circle Ranking

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Solution Overview

Problem

Organizations face challenges in tracking and sharing knowledge and expertise among members due to influx of new members, skill set modifications, and decentralization, leading to outdated knowledge repositories and low usage by members.

Innovation Solution

Systems and methods for notifying users of content creation related to existing content expertise by evaluating content to determine topics, monitoring user activity to assess knowledge levels, and ranking users based on collaboration circles to identify and notify experts of relevant content creation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If a knowledge repository is maintained by an organization, then knowledge can be stored and shared, but members may not remember to use it or choose not to use it for various reasons

Engineering Contradiction:

Improveknowledge sharingVSAvoidusage by members

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The system automatically monitors user activity, evaluates content against user expertise, and notifies relevant users without requiring manual intervention. This self-service approach eliminates the need for members to remember to use the knowledge repository, as the system proactively delivers relevant content to them based on their demonstrated knowledge levels and collaboration patterns.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system implements a feedback loop by monitoring user interactions with content, determining knowledge levels based on this activity, and using this information to notify users of new content relevant to their expertise areas. This continuous feedback mechanism ensures that the knowledge repository remains actively used by members who are most likely to benefit from and contribute to the shared knowledge.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If user activity is monitored to determine knowledge levels, then expertise can be accurately identified, but system complexity increases

Engineering Contradiction:

Improveknowledge level assessmentVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system determines user knowledge levels by automatically monitoring and analyzing user activity within the existing collaboration platform. This approach leverages naturally occurring user behavior data without requiring additional surveys, tests, or manual assessments, thereby achieving precise knowledge level measurement while minimizing the increase in system complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses the same user activity monitoring infrastructure that already exists for collaboration purposes and repurposes it to determine knowledge levels. By making the monitoring system multi-functional (serving both collaboration tracking and expertise assessment), the patent avoids duplicating infrastructure and reduces the overall complexity increase.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Measurement precision

If collaboration circles are determined based on user interactions, then relevant experts can be identified, but data processing requirements increase

Engineering Contradiction:

Improveexpert identificationVSAvoiddata processing

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The system extracts only the essential interaction data needed to determine collaboration circles and knowledge levels, rather than processing all user activity data. By selectively extracting relevant interaction patterns (such as co-authorship, commenting, and reviewing behaviors), the system achieves precise expert identification while minimizing the quantity of data that requires processing.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system segments user interactions into distinct types (collaboration activities, content creation, content consumption) and processes each segment separately to determine different aspects of user expertise. This segmentation allows for more efficient data processing by focusing on specific interaction patterns relevant to knowledge level assessment rather than analyzing all user data uniformly.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20230385769A1Notifying content expert of content created by user outside collaboration circle of content expert

Publication Date: 2023.11.30 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Examples of the present disclosure describe systems and methods for notifying users of content creation related to existing content expertise. In examples, content associated with a data domain is evaluated to determine the topics associated with the content. User activity for the data domain is monitored to determine user knowledge levels on various topics. User collaboration circles are determined based on interactions between users. When new content is detected, topics in the new content are evaluated and users having knowledge on the topics are identified based on the determined knowledge levels. The users having knowledge on the topics are ranked based in part on their collaboration circles. At least a portion of the ranked users having knowledge on the topics are notified of the new content creation and/or the users creating the new content are notified of the ranked users having knowledge on the topics.