Relevance-Prioritized Data Dimension Presentation

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Solution Overview

Problem

Conventional online systems face challenges in managing and presenting high-dimensional data to users, as they often present all dimensions or a truncated list based on metadata, rather than relevance, hindering user experience and making it difficult for users to determine which dimensions are relevant for their tasks.

Innovation Solution

An online system determines the relevance of data dimensions to users by analyzing historical usage, data changes, and schema analysis, prioritizing and presenting only the most relevant dimensions, thereby improving user experience and minimizing distractions from irrelevant data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If conventional online systems present all dimensions or a truncated list based on metadata, then completeness of data presentation is improved, but user experience deteriorates due to difficulty in determining relevant dimensions

Engineering Contradiction:

Improvecompleteness of data presentationVSAvoiduser experience

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The system extracts and prioritizes only the most relevant dimensions from the complete data set based on relevance scoring, presenting a filtered subset to users while maintaining access to all dimensions if needed. This resolves the contradiction by separating the complete data repository from the user-facing presentation layer.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system applies different quality levels to different dimensions by prioritizing and highlighting relevant dimensions in the user interface, while less relevant dimensions are de-emphasized or hidden. This allows the presentation to adapt locally to user needs while preserving the complete data set.

Inventive Principle:

Principle #3Local quality

2Loss of information

If conventional online systems present all dimensions to users, then data completeness is improved, but user distraction from irrelevant data increases

Engineering Contradiction:

Improvedata completenessVSAvoiduser distraction

Core Design Contradiction:

Loss of informationVSObject-affected harmful factors

Solution Approach 1:

The system extracts and presents only the most relevant dimensions to users based on relevance analysis, removing irrelevant dimensions from the primary view. This eliminates user distraction from irrelevant data while preserving access to the complete data set for users who need it.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary relevance analysis and dimension prioritization before presenting data to users, pre-filtering the information based on predicted user needs and historical behavior. This preliminary action prevents users from being overwhelmed by irrelevant dimensions in the first place.

Inventive Principle:

Principle #10Preliminary action

3Ease of operation

If conventional online systems present a truncated list of dimensions, then user experience is improved by reducing information overload, but loss of relevant information increases

Engineering Contradiction:

Improveuser experienceVSAvoidrelevant data availability

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The system implements feedback mechanisms where user interactions with prioritized dimensions are tracked and used to refine future relevance scoring. This ensures that the truncated presentation continues to provide relevant information by adapting to actual user behavior patterns.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically adjusts the set of presented dimensions based on user context, behavior, and changing requirements. The truncated list is not static but adapts over time to maintain relevance, ensuring that the most currently important dimensions are always prioritized.

Inventive Principle:

Principle #15Dynamics

4Device complexity

If conventional online systems present dimensions based on metadata, then system complexity is reduced, but relevance accuracy deteriorates

Engineering Contradiction:

Improvesystem complexityVSAvoidrelevance accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system introduces an intermediary relevance scoring layer between the metadata and the dimension presentation. This intermediary layer uses multiple signals including user behavior, historical data, and contextual information to compute relevance scores, improving accuracy without requiring complete redesign of the underlying system architecture.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10831757B2High-dimensional data management and presentation

Publication Date: 2020.11.10 SALESFORCE INC

AI summary

An online system manages data by determining relevance of data dimensions to users. The online system determines which data dimensions a user is likely to be interested in. If a user requests to access a data set that includes data of different dimensions, the online system analyzes the dimensions' relevance to the user before providing the data set to the user. The online system provides the data to the user by prioritizing data dimensions that are more relevant to the user. As such, the online system improves the user experience by allowing users to conveniently and quickly locate relevant data and minimizing the distraction caused by irrelevant data. The online system may create and provide a user interface to present data dimensions that are determined to be relevant.