Automatic Metadata Generation for Digital Content via Virtual Calendar
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Solution Overview
Problem
The manual process of adding descriptive metadata to digital content items is inefficient and time-consuming, especially with the increasing volume of content generated by users, as existing applications do not support bulk metadata addition or automatic generation, hindering search, organization, and enjoyment of content.
Innovation Solution
A system and method that utilize a device's hardware processor to obtain event information from a virtual calendar, detect objects in content items, receive audio information, and generate metadata based on biometric data, allowing for automatic or semi-automatic association of metadata with content items, enabling bulk metadata addition and improved organization and search capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual metadata entry is used for each content item, then metadata accuracy and completeness are improved, but time consumption and labor requirements increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically generating metadata before content creation or immediately upon creation. Event information is obtained from virtual calendars in advance, and metadata is pre-generated based on detected objects, audio information, and biometric data, eliminating the need for manual entry after content creation.
Solution Approach 2:
The system enables self-service by automatically generating and associating metadata with content items without requiring manual user intervention. The automated system detects objects, processes audio information, and generates metadata independently, allowing the content management system to serve itself rather than requiring user labor.
2Productivity
If bulk metadata addition is supported, then productivity is improved, but system complexity increases
Solution Approach 1:
The system achieves universality by implementing a multi-functional metadata generation system that handles multiple content types (images, video, audio) and multiple metadata sources (event information, object detection, audio processing, biometric data) through a single integrated framework, allowing bulk operations across diverse content without requiring separate specialized systems.
Solution Approach 2:
The system uses an intermediary approach by introducing a virtual calendar and centralized metadata generation module that mediates between various data sources (event information, detected objects, audio information) and the final metadata output, coordinating complex operations through a structured intermediate layer rather than direct complex interactions.
3Loss of time
If automatic metadata generation is implemented, then time consumption is reduced, but metadata quality and relevance may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where detected objects, audio information, and biometric data are processed to generate metadata that is then associated with content items. The system continuously refines metadata generation based on the feedback from these multiple data sources, ensuring quality while maintaining automation.
Solution Approach 2:
The system applies parameter changes by dynamically adjusting metadata generation based on different content types and detected characteristics. The virtual calendar provides temporal parameters, object detection provides visual parameters, audio information provides acoustic parameters, and biometric data provides identification parameters, allowing the system to adapt metadata generation to specific content characteristics while remaining automated.
Data Source
AI summary
Methods, computer-readable media, and systems for scheduling the association of metadata with content. In an embodiment, event information is obtained from a virtual calendar, wherein the event information comprises at least one event detail and one or more parameters defining a time period. First metadata is generated based on the event detail, and is stored, in association with the time period, in a memory. Then, subsequently, during the time period, the first metadata may be retrieved from the memory, and associated with one or more content items generated on the device.