Mentor Application for Personalized Software Assistance
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Solution Overview
Problem
Conventional software applications lack the ability to automatically account for different experience levels and domain-specific knowledge of users, leading to reduced effectiveness in providing personalized assistance for specific help requests.
Innovation Solution
A computer-implemented method that generates a help request, computes match scores based on user contexts to identify suitable users, and establishes a connection for an interactive help session, prioritizing users with relevant experience and knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional software applications provide generalized assistance through documentation and training classes, then users can obtain basic software knowledge, but users cannot obtain personalized guidance for specific tasks or troubleshooting
Solution Approach 1:
The system automatically generates help requests based on user actions and context without requiring users to manually search for help. The system self-identifies when assistance is needed and initiates the help-seeking process autonomously.
Solution Approach 2:
The system introduces an intermediary layer that matches help requests with appropriate users based on computed match scores. This intermediary mechanism connects users needing help with potential helpers without direct user-to-user initiation.
2Adaptability or versatility
If users ask for one-on-one help directly or seek help via centralized help organizations, then personalized guidance can be obtained, but it is difficult to identify someone with the specific experience or domain-specific knowledge needed
Solution Approach 1:
The system replaces manual identification of helpers with an automated computational process. Match scores are computed algorithmically based on user contexts and help request characteristics, substituting human judgment with systematic automated assessment.
Solution Approach 2:
User contexts are pre-computed and stored before help requests occur. This preliminary preparation of user information enables rapid matching when help is needed, avoiding time-consuming identification processes at the moment help is required.
3Productivity
If conventional software automatically pairs users with helpers, then help requests can be processed efficiently, but the system cannot account for different experience levels and domain-specific knowledge of users
Solution Approach 1:
The system evaluates user expertise locally for each specific help request rather than using general user profiles. Match scores are computed based on the intersection of user context and specific help request requirements, ensuring precise assessment of relevant expertise for each situation.
Solution Approach 2:
The system dynamically computes match scores as a parameter that reflects the suitability of potential helpers for specific help requests. This parameter changes based on the help request characteristics and user context, enabling flexible and precise matching beyond static user classifications.
Data Source
AI summary
In various embodiments, a mentor application automatically obtains assistance with software applications. The mentor application generates a computer-generated help request associated with a first user of a software application. Based on the computer-generated help request and a set of user contexts associated with a set of users, the mentor application computes match scores. Each match score predicts how suitable a particular user is for servicing the computer-generated help request. Based on the match scores, the mentor application transmits at least one help request notification to at least one user included in the set of users to determine a second user to service the computer-generated help request. The mentor application then establishes a computer connection between the first user and the second user through which an interactive help session between the first user and the second user is held.