Multi-layered Data Model for Audience-Specific Image Selection
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Solution Overview
Problem
Current systems for generating documents for multiple audiences are time-consuming and expensive, as they lack intelligent selection, positioning, and titling of images based on language, regional, regulatory, and cultural differences, leading to duplicate data entry and formatting issues across various media types.
Innovation Solution
A multi-layered data model with rule-based inheritance allows for rapid determination of image choice across audience-specific documents, utilizing an audience hierarchy to minimize data entry and maintenance, and automatically updating information for multiple audiences, with visual representations to indicate inheritance levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current systems are used to generate documents for multiple audiences, then documents can be published in multiple languages and media types, but the process is time-consuming and expensive requiring large amounts of duplicate data entry
Solution Approach 1:
The patent segments the document data into multiple hierarchical layers (global layer, audience-specific layers, image-specific layers) that can be independently managed and inherited. This segmentation allows data to be organized by audience characteristics (language, region, culture, regulations) enabling efficient reuse across multiple audiences without duplicate entry
Solution Approach 2:
The system performs preliminary action by pre-defining audience hierarchies and inheritance rules before document generation. Image pools are pre-configured with audience-specific criteria, and the system automatically determines appropriate images based on audience characteristics, eliminating the need for manual image selection for each document instance
2Adaptability or versatility
If current systems are used to generate documents for multiple audiences, then documents can be published in multiple languages and media types, but large amounts of duplicate operator entries are required for similar languages, cultural, regional or regulatory specific embodiments
Solution Approach 1:
The patent implements universality through a unified data model that handles multiple languages, regions, cultures, and regulations within a single hierarchical structure. The global layer contains universal data that can be inherited by all audience-specific layers, while image pools serve multiple audiences with automatic selection based on audience characteristics, reducing data entry complexity
Solution Approach 2:
The system adds dimensional organization to document data by introducing hierarchical layers (global, audience-specific, image-specific) and audience characteristic dimensions (language, region, culture, regulations). This multi-dimensional structure allows efficient data reuse across similar audiences while maintaining specificity where needed
3Adaptability or versatility
If current systems are used to generate documents for multiple audiences, then documents can be published in multiple media types, but formatting the document for each media type is time consuming and requires large amounts of maintenance
Solution Approach 1:
The patent uses parameter changes to adapt documents for different media types by modifying audience hierarchy configurations and image pool settings rather than creating separate formatting systems. The same multi-layered data model serves multiple media types with automatic adaptation based on audience and media parameters, reducing maintenance requirements
4Ease of operation
If current systems are used for image selection, then images can be selected for documents, but selection of images based on the intended audience is generally performed by hand and no visual clues are provided as to the images used or missing
Solution Approach 1:
The patent implements feedback by providing visual indicators in the user interface that show which images are currently selected, which are missing, and their inheritance status. The system automatically determines appropriate images based on audience characteristics and provides visual feedback to confirm compliance with audience expectations, eliminating manual verification time
Data Source
AI summary
A multi-layered data model for determining image choice across a set of audience-specific documents comprising language, regional, regulatory and/or cultural differences. Enables generation of audience-specific documents with audience specific images and audience-specific image placement based on inheritance of images and image metadata associated with hierarchical audiences. For data entry, enables a user to rapidly determine if images in an audience specific document conform to the expectations or requirements of an intended audience. The data entry and edit interface distinguishes between current and inherited audience levels through the use of color or any other mechanism that allows a user to quickly identify data that is missing and needs to be populated, changed or remain unchanged if the inherited image or image title or placement is suitable for the given audience. Documents are generated to any number of media types such as HTML, XML and paper.