Automatic Filter Criteria Generation for Large Datasets

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Solution Overview

Problem

Manually entering filter criteria for large datasets is laborious and time-consuming, especially when dealing with numerous objects and fields in database applications.

Innovation Solution

A method that automatically generates filter criteria by comparing field values across selected objects, using algorithms tailored to each data type, to create a filter that can be applied to the dataset, reducing manual effort and increasing efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual filter criteria entry is used, then filter creation is simple and direct, but the process becomes laborious and time-consuming with large datasets

Engineering Contradiction:

Improvefilter creation speedVSAvoidtime spent on manual filter criteria entry

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs self-service by automatically analyzing the dataset structure and generating filter criteria without requiring manual user input. The database management system itself identifies common field values and creates filter expressions, eliminating the need for users to manually parse and enter filter criteria.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual mechanical process of entering filter criteria is replaced with an automated computational system. The system uses algorithms to analyze field values, identify patterns, and generate filter criteria automatically, substituting human manual operations with machine-based automation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automatic filter criteria generation is implemented, then productivity increases and time is reduced, but system complexity increases

Engineering Contradiction:

Improvedata filtering efficiencyVSAvoidcomplexity of automatic filter generation system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The automatic filter generation process is segmented into distinct operational stages: data analysis phase where field values are examined, pattern recognition phase where common values are identified, and filter creation phase where criteria are generated. This segmentation manages complexity by breaking down the automated process into manageable, sequential steps.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary automated analysis layer between the user and the filter creation process. This intermediary automatically processes the dataset, identifies filtering opportunities, and presents generated filter criteria to the user, mediating between raw data and final filter application while managing system complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10185478B2Creating a filter for filtering a list of objects

Publication Date: 2019.01.22 SAP SE

AI summary

Various embodiments of system and methods of creating a filter for a list of objects are described herein. The method includes receiving a selection of a set of objects from the list of objects composed of one or more fields having field values, and comparing the field value in each field of an object with the field values in each of the corresponding fields of the other objects in the set of objects. Based on the comparison, identifying that the field values are the same across the one or more fields of the set of objects. The method further includes generating a list of filter criteria based on the identified field values. The filter may be created using the list of filter criteria.