Cognitive Auto-fill for Electronic Documents

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Solution Overview

Problem

Completing complex electronic documents, such as spreadsheets and forms, is time-consuming and frustrating due to the need for manual entry of repetitive information across multiple documents, especially when similar information is required in a short time frame.

Innovation Solution

Implementing a cognitive auto-fill functionality that utilizes user data and contextual analysis to recommend entries for fillable fields in electronic documents, leveraging structured and unstructured data sources, including sensors and social media activity, to automate the filling process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual entry is used to complete electronic documents, then information can be accurately entered, but the process becomes time-consuming and inefficient

Engineering Contradiction:

Improvedocument completion speedVSAvoidtime spent on manual entry

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system automatically collects data from multiple sources (databases, sensors, social media, web crawls) and uses cognitive analysis to self-generate recommended entries for document fields without requiring manual user input, thereby resolving the contradiction between accurate information entry and time efficiency

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary data collection and cognitive analysis to pre-generate recommended entries before the user needs to complete the document, so that when the user needs to fill fields, the recommendations are already prepared and ready for immediate use

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If cognitive analysis with multiple data sources is implemented, then auto-fill accuracy improves, but system complexity increases

Engineering Contradiction:

Improveauto-fill recommendation accuracyVSAvoidsystem architecture complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the complex data collection and analysis process into distinct modules: data collection module (gather data from multiple sources), data processing module (clean and structure data), cognitive analysis module (analyze and generate recommendations), and recommendation module (present to user). This segmentation manages complexity while maintaining high accuracy through specialized processing at each stage

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediate processing layers including data normalization services, cognitive analysis engines, and recommendation filtering mechanisms that mediate between raw multi-source data and final recommendations, simplifying the overall system architecture while improving accuracy through structured intermediate processing

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11501059B2Methods and systems for auto-filling fields of electronic documents

Publication Date: 2022.11.15 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

Embodiments for managing an electronic document by one or more processors are described. An entry for a first of a plurality of fillable fields of an electronic document is received. A recommended entry for at least a second of the plurality of fillable fields is determined based on at least one data source associated with a user. A signal representative of the determined recommended entry for the at least a second of the plurality of fillable fields is generated.