Context-Aware Multimedia Tag Recommendation System
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Solution Overview
Problem
Existing solutions for tagging multimedia content are often inaccurate or incomplete, as they rely on user inputs and fail to account for context, leading to inefficient identification of subject matter in multimedia content.
Innovation Solution
A method and system that generate signatures for multimedia content elements, correlate them to determine context, and recommend tags based on contextually related content elements, using a processing circuitry and memory to execute the process of obtaining, correlating, and identifying tags for accurate recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual tagging solutions are used, then user input flexibility is improved, but tagging accuracy and completeness deteriorate
Solution Approach 1:
The patent introduces an automatic tagging system as an intermediary between the user and the tagging process. The system analyzes multimedia content elements (images, videos, audio) and automatically generates tag recommendations based on content analysis, thereby improving tagging accuracy while maintaining user flexibility in selecting or modifying tags.
Solution Approach 2:
The system enables self-service automatic tagging by analyzing the multimedia content itself to generate relevant tags without requiring manual user input for each tag. The content analyzes for itself and generates appropriate tags, improving both accuracy and efficiency while users retain the option to review and adjust if needed.
2Productivity
If automatic tagging solutions are used, then tagging efficiency is improved, but context understanding capability deteriorates
Solution Approach 1:
The patent segments the tagging process into multiple independent analysis components: visual content analysis, audio content analysis, text analysis, and context correlation. Each component processes specific aspects of the multimedia content and generates separate results that are then integrated, allowing the system to maintain high efficiency while capturing comprehensive contextual information.
Solution Approach 2:
The system adds a contextual dimension to traditional automatic tagging by analyzing relationships between multiple content elements and their surrounding context. Instead of simply tagging individual elements, the system considers how elements relate to each other and to the overall context, thereby improving context understanding while maintaining automation efficiency.
3Speed
If superficial subject matter recognition is used, then processing speed is improved, but tagging completeness deteriorates
Solution Approach 1:
The patent implements preliminary rapid analysis to generate initial tags quickly, then performs subsequent contextual correlation and refinement steps. The system first identifies obvious subject matter at high speed, then enriches the tagging by analyzing relationships between multiple content elements and their context, ensuring both speed and completeness are achieved through staged processing.
Data Source
AI summary
A system and method for recommending tags for a multimedia content element to be tagged. The method includes obtaining a plurality of signatures for the multimedia content element to be tagged, wherein each of the generated signatures represents a concept, wherein each concept is a collection of signatures and metadata representing the concept; correlating between the plurality of signatures to determine at least one context of the multimedia content element to be tagged; searching for at least one contextually related multimedia content element, wherein each contextually related multimedia content element matches at least one of the determined at least one context; and identifying at least one tag, wherein each identified tag is associated with at least one of the at least one contextually related multimedia content element; generating a recommendation including the identified at least one tag.