Solution Keyword Tag Cloud for Support Forum Analytics

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Solution Overview

Problem

Customers face difficulties in finding effective solutions to product or service issues due to the lack of clarity and relevance in existing tagging methods for online support forums, leading to increased support costs and user frustration.

Innovation Solution

A computer-implemented method generates a solution keyword tag cloud that matches user queries with condition-solution trees, ordering solutions by success rate and risk, and updates the cloud based on user interactions, while providing a solution context-clearness index to guide users towards the correct solution and automatically posting a tagged question when no solution is found.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual social tagging of posts with meaningful keywords is used, then the relevance of tags to user issues is improved, but the time and effort required to create and maintain tags increases

Engineering Contradiction:

Improvetag relevanceVSAvoidtime to create tags

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables self-service by automatically generating tags through AI analysis of post content, eliminating the need for manual tagging while maintaining high relevance. The AI model autonomously processes support posts and generates appropriate tags without human intervention.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of tagging with an automated AI-based system. The mechanical action of manually assigning tags is substituted with computational algorithms that automatically analyze post content and generate relevant tags.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of time

If computer automatic tagging of posts with simple keywords is used, then the time required to tag posts is reduced, but the meaningfulness and helpfulness of tags decreases

Engineering Contradiction:

Improvetime to tag postsVSAvoidtag meaningfulness

Core Design Contradiction:

Loss of timeVSMeasurement precision

Solution Approach 1:

The system changes the parameters of automatic tagging by using advanced AI models that analyze semantic meaning, context, and relationships in post content. This transforms simple keyword matching into intelligent tag generation that maintains both speed and meaningfulness.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The tagging system combines multiple AI techniques including natural language processing, semantic analysis, and contextual understanding to create a composite tagging approach that achieves both automation and meaningfulness.

Inventive Principle:

Principle #40Composite materials

3Reliability

If customers read through a large number of tagged posts to find solutions, then comprehensive solution coverage is achieved, but the time required to find relevant solutions increases

Engineering Contradiction:

Improvesolution coverageVSAvoidtime to find solution

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system extracts and highlights only the most relevant tags and solutions based on AI analysis of user queries, removing the need to scan through all tagged posts. This extraction process delivers comprehensive solution coverage by focusing on high-probability matches.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system uses feedback from user interactions, query patterns, and solution effectiveness to continuously refine tag relevance and prioritize displayed results, reducing search time while maintaining comprehensive coverage.

Inventive Principle:

Principle #23Feedback

4Ease of operation

If support personnel are increased to assist customers with product issues, then customer support quality is improved, but operational costs increase

Engineering Contradiction:

Improvecustomer support qualityVSAvoidsupport personnel

Core Design Contradiction:

Ease of operationVSQuantity of substance

Solution Approach 1:

The system empowers customers to self-diagnose and resolve issues through AI-generated tags and organized solutions, reducing dependency on human support personnel while maintaining high support quality.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The AI tagging system acts as an intermediary between customers and support personnel, handling routine classification and organization tasks, which allows human support staff to focus on complex issues requiring human judgment.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11645335B2Generating solution keyword tag clouds based on support forum post analytics

Publication Date: 2023.05.09 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

Generating a solution keyword tag cloud is provided. The solution keyword tag cloud is generated for a product based on matching keywords identified in a question asking how to resolve an issue experienced by a user with the product with keyword tags included in a set of condition-solution trees corresponding to the product. In response to receiving an indication that a tried solution in the solution keyword tag cloud did not resolve the issue experienced by the user, the solution keyword tag cloud is graphically updated by moving the tried solution that failed to resolve the issue from a solution section of the solution keyword tag cloud to a condition section of the solution keyword tag cloud. The solution keyword tag cloud is presented in a graphical user interface display on a client device corresponding to the user.