Software Recommendation System Using Data Normalization

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Solution Overview

Problem

Conventional software management systems fail to provide effective guidance for selecting and configuring software that suits the specific needs of organizations, leading to the implementation of unsuitable software tools, which can result in inefficiencies, increased costs, and reduced productivity.

Innovation Solution

A software management apparatus that converts event data from multiple software systems into a common format using a data normalizing layer, computes ratings for software systems based on predicted organization output, and provides configuration recommendations, utilizing a machine learning model trained on data from various organizations to recommend suitable software tools and configurations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional software management systems are used, then software can be implemented, but the systems cannot provide useful guidance regarding which software an organization should implement, leading to selection of unsuitable software

Engineering Contradiction:

Improvesoftware selection accuracyVSAvoidsoftware suitability information

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The system segments software evaluation into multiple dimensions including organizational characteristics, software features, and performance metrics. By breaking down the complex selection process into manageable segments, the system can provide precise guidance on software suitability for different organizational contexts.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements feedback mechanisms that analyze software performance data and organizational outcomes to continuously improve software recommendations. By incorporating feedback from actual software usage and organizational results, the system refines its ability to accurately match software to organizational needs.

Inventive Principle:

Principle #23Feedback

2Productivity

If software is selected without proper guidance, then implementation can proceed, but inefficiencies, increased costs, and reduced productivity occur

Engineering Contradiction:

Improveorganizational productivityVSAvoidsoftware implementation costs

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The system performs preliminary analysis and evaluation of software suitability before implementation. By assessing organizational characteristics and matching them with appropriate software features in advance, the system prevents costly implementation mistakes and ensures productive software selection from the outset.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces manual, trial-and-error software selection processes with an automated analytical system. This substitution of mechanical decision-making with intelligent analysis reduces implementation costs and improves productivity by selecting the right software on the first attempt.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If data from multiple software systems with different formats is analyzed, then comprehensive software ratings can be computed, but data conversion and normalization are required

Engineering Contradiction:

Improvesoftware system compatibilityVSAvoiddata conversion complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements a universal data normalization framework that can handle multiple software system formats through a single common data structure. This universal approach allows the system to process data from diverse sources without requiring separate conversion mechanisms for each format, reducing overall complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system introduces a data normalization layer as an intermediary between diverse software systems and the analysis engine. This intermediary translates various data formats into a common structure, enabling comprehensive software ratings while managing conversion complexity through a dedicated intermediary component.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11775286B2Systems industry benchmarking and corporation systems tool recommendation

Publication Date: 2023.10.03 ADOBE INC

AI summary

Systems and methods for software management are described. One or more embodiments of the present disclosure receive first organization data about a first organization that uses a first software system and second organization data about a second organization that uses a second software system; receive first event data from the first organization and second event data from the second organization; generate first converted event data and second converted event data by converting the first event data and the second event data to a common data format; predict organization output based on using the first software system and based on using the second software system; compute a first rating for the first software system and a second rating for the second software system for use in the third organization; and installing the first software system in a computer system of a third organization based on the first rating.