Multimedia Data Name Recognition via Knowledge Base Filtering
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Solution Overview
Problem
Existing technologies face challenges in efficiently processing and understanding intercepted partial multimedia data, as they lack effective methods to recognize the name of the multimedia data to which the intercepted partial data belongs.
Innovation Solution
A method is provided that involves recognizing multimedia data to obtain key information, querying a predetermined knowledge base to determine a multimedia name and association degree, and determining the multimedia data name based on similarity with alternative data when the association degree is below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to process intercepted partial multimedia data, then the processing can be completed, but the accuracy of recognizing the multimedia data name is low and processing efficiency is poor
Solution Approach 1:
The patent segments the multimedia data processing into multiple stages: initial recognition to obtain key information, knowledge base querying to find candidate names, similarity comparison to evaluate alternatives, and final determination. This segmentation allows each stage to focus on specific tasks, improving both accuracy and efficiency by avoiding unnecessary processing of irrelevant data.
Solution Approach 2:
The patent performs preliminary actions by first querying the knowledge base with key information extracted from the multimedia data to obtain candidate names and their association degrees. This preliminary filtering step eliminates obviously irrelevant data before performing more computationally intensive similarity comparisons, thereby improving processing efficiency while maintaining accuracy.
2Reliability
If all alternative multimedia data are processed to determine the correct name, then comprehensive comparison is achieved, but processing time and computational resources increase significantly
Solution Approach 1:
The patent applies local quality by differentiating the processing depth for different candidate names based on their association degrees. Candidates with high association degrees undergo more rigorous similarity comparison, while those with low association degrees are quickly filtered out. This selective processing ensures reliability for promising candidates while minimizing time loss on unlikely matches.
Solution Approach 2:
The patent uses the association degree as a parameter to dynamically adjust the processing strategy. When the association degree exceeds a threshold, the system performs detailed similarity comparison; when it falls below the threshold, the system quickly discards the candidate. This parameter-based decision-making balances reliability and processing time effectively.
Data Source
AI summary
A method of processing multimedia data, a device, and a medium, which relates to a field of an artificial intelligence technology, in particular to fields of knowledge graph and deep learning. The method of processing the multimedia data includes: recognizing the multimedia data so as to obtain at least one key information of the multimedia data; querying a predetermined knowledge base according to the at least one key information, so as to determine a multimedia name associated with the at least one key information and an association degree between the multimedia name and the at least one key information; and determining, in the multimedia name, a name of the multimedia data based on a similarity between alternative multimedia data for the multimedia name and the multimedia data, in response to the association degree being less than a first threshold value.