Multimedia Concept Database Enrichment via Signature Matching
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Solution Overview
Problem
Current multimedia data search systems face challenges in effectively representing and comparing multimedia content due to its abstract and complex nature, leading to inefficiencies in storage, management, and search functionality, especially with the exponential growth of Internet content.
Innovation Solution
A method and system for enriching a concept database by generating signatures for multimedia data elements, matching them to existing concepts, and generating reduced representations to improve search efficiency and memory utilization, allowing for the extraction of new knowledge and scalable data handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multimedia data is stored and managed using traditional metadata approaches, then search functionality is provided, but the abstract and complex nature of multimedia content leads to inadequate representation and poor search accuracy
Solution Approach 1:
The patent creates simplified copies of multimedia content through concept databases that store condensed representations (concepts) instead of the full complex data. These concepts are generated by extracting essential features from multimedia data, creating a reduced representation that maintains searchability while eliminating complexity. The concept database stores these simplified copies, enabling accurate search without requiring the original complex multimedia data to be processed during search operations.
Solution Approach 2:
The patent extracts essential information from complex multimedia data by generating concepts that capture the salient features. The system extracts key characteristics from images, video, or audio and stores them as discrete concepts in the concept database. This extraction process separates the essential searchable information from the redundant complex data, allowing for precise search based on extracted concepts rather than the full complex multimedia content.
2Measurement precision
If the concept database is enriched with more concepts to improve search accuracy, then classification precision improves, but the size of the database and computational resources required increase
Solution Approach 1:
The system extracts only the essential concepts from multimedia data rather than storing all possible information. By identifying and extracting only the salient features that are necessary for accurate classification and search, the patent creates a compact concept database that achieves high precision without requiring storage of all possible data variations. This selective extraction ensures that only meaningful concepts are added to the database.
Solution Approach 2:
The patent implements a self-service enrichment mechanism where the system automatically generates and adds concepts to the database based on the multimedia data it processes. Rather than requiring manual curation or pre-defined concept lists, the system autonomously extracts concepts from the data itself and integrates them into the concept database. This self-service approach ensures that the database grows with only the concepts actually present in the multimedia content, avoiding unnecessary expansion.
Data Source
AI summary
A system and method for enriching a concept database. The method includes determining, based on at least one signature of a first multimedia data element (MMDE) and signatures of a plurality of existing concepts in the concept database, at least one first concept among the plurality of existing concepts, wherein each of the at least one first concept matches a portion of the at least one signature of the first MMDE; generating a reduced representation of the first MMDE, wherein generating the reduced representation further comprises removing the portion of the first MMDE matching the at least one first concept; comparing the reduced representation of the first MMDE to signatures representing a plurality of second MMDEs to determine a plurality of matching second MMDEs; generating, based on the reduced representation of the first MMDE and the plurality of matching second MMDEs, at least one second concept; and adding the generated at least one second concept to the concept database.