Automated Digital Artifact Generation via Machine Learning
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Solution Overview
Problem
Users face a time-consuming and labor-intensive process when generating digital artifacts from abundant digital items, such as photos, as they need to manually select and arrange meaningful content, which can prevent them from creating digital representations like photobooks.
Innovation Solution
A computer system that automatically generates digital artifacts using machine learning algorithms to extract metadata, filter and decimate digital items, and arrange them in a meaningful layout with minimal user interaction, allowing for the creation of digital artifacts like photobooks without the need for extensive user input or internet connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users manually select and arrange digital items to create digital artifacts, then the quality and meaningfulness of the artifact can be ensured, but the time and labor required increases significantly
Solution Approach 1:
The system performs automatic selection and arrangement of digital items using machine learning algorithms, allowing the system to serve itself in creating digital artifacts without requiring manual user intervention for each selection and arrangement decision
Solution Approach 2:
The patent replaces the manual mechanical process of selecting and arranging digital items with an automated machine learning-based system that uses algorithms to determine meaningful representations and optimal arrangements
2Reliability
If users manually curate digital items to represent a story or trip, then the relevance and coherence of the artifact is improved, but the complexity of the process increases
Solution Approach 1:
The patent replaces complex manual curation processes with automated machine learning algorithms that analyze metadata, timestamps, locations, and content to automatically determine relevance and coherence of digital items for the artifact
Solution Approach 2:
The system extracts relevant features and metadata from digital items automatically, separating the complex analysis task from the user and performing it through algorithmic processing to determine which items should be included
3Measurement precision
If the system processes all digital items to ensure quality selection, then the accuracy of artifact generation is improved, but the computational resources and time required increases
Solution Approach 1:
The system extracts and processes only relevant metadata and features from digital items rather than analyzing the complete content of each item, reducing computational overhead while maintaining selection accuracy through targeted feature analysis
Solution Approach 2:
The patent applies partial processing by analyzing only the necessary subset of digital item attributes (metadata, timestamps, locations) required for meaningful selection, rather than performing exhaustive analysis on all possible characteristics
4Ease of operation
If the system presents incremental results during generation, then user engagement and experience are improved, but the total processing time perceived by the user increases
Solution Approach 1:
The system performs periodic updates by presenting incremental results at regular intervals during the artifact generation process, allowing users to observe progress and engage with the creation process without waiting for complete processing
Solution Approach 2:
The patent implements feedback mechanisms by showing users progressive results during generation, allowing users to observe how the system is selecting and arranging items, which enhances engagement and provides visibility into the automated decision-making process
Data Source
AI summary
A method and system are described to facilitate the generation, and/or presentation, of digital artifacts, to a client device associated with a user. Metadata is extracted from a plurality of digital items; a subset of the digital items is selected based at least in part on the extracted metadata; the subset is filtered based at least in part on a predetermined rule; a parameter is estimated that is associated with a set of resulting digital items for the digital artifact; the filtered subset of digital items filtered is decimated based at least in part on the parameter and a respective quality assessment of each of the filtered subset of digital items; and the digital artifact is generated by arranging a remainder of digital items from the plurality of digital items based at least in part on a preselected layout, and presenting the digital artifact to a user on a display of the user device, wherein a subset of the digital artifact generated in is presented to the user prior to completion of the generation.