Multimedia Segment Hashing for Activity Linkage
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Solution Overview
Problem
There is a need for improved systems and methods that enable better collaboration between content creators and consumers, and for content creators to receive detailed feedback to enhance their content, particularly in managing conversations linked to multimedia content.
Innovation Solution
An electronic data processing system and method that manages conversations linked to multimedia content divided into segments, using processors to determine hash values for frames, identify edited content, associate activities with corresponding segments, and analyze subject matter, facilitating feedback and engagement analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multimedia content is edited after activities are submitted, then the content is improved or updated, but the linkage between activities and content segments becomes broken or inaccurate
Solution Approach 1:
The system performs preliminary actions by generating and storing hash values for each segment of the multimedia content before any editing occurs. When content is edited, these pre-stored hash values serve as a baseline for detecting changes and automatically updating activity linkages, eliminating the need for manual re-linking and maintaining accuracy despite content modifications.
Solution Approach 2:
The system implements a feedback mechanism where hash values are continuously compared between the original and edited content. When discrepancies are detected through hash comparison, the system automatically triggers updates to the activity data structures, creating a closed-loop system that maintains linkage accuracy through continuous monitoring and self-correction.
2Measurement precision
If hash values are determined for every frame in each segment, then content change detection precision is improved, but computational complexity and processing time increase
Solution Approach 1:
The multimedia content is divided into discrete segments, and hash values are generated for each segment rather than processing the entire content as a single unit. This segmentation allows for localized change detection, reducing the computational scope from the entire multimedia file to individual segments, thereby lowering overall computational complexity while maintaining detection precision.
Solution Approach 2:
Instead of processing every single frame with equal depth, the system uses hash functions that provide sufficient precision for change detection without the excessive computational overhead of analyzing every frame in detail. The hash values capture essential content characteristics while using fewer computational resources than full frame-by-frame analysis.
Data Source
AI summary
An activity management system is configured to allow users to access multimedia content where the multimedia content is divided in to segments. While a user is viewing or interacting with the multimedia content, the user can submit one or more activities (e.g., comments, questions, replies, or reactions) using a graphical user interface. The system is operable to electronically link the activity provided by the user with the particular segment of multimedia content in which the activity was captured by the system. The system is also configured to determine a sentiment score for particular multimedia content, one or more segments of the particular multimedia content, a user, a group of users, or an organization. The sentiment score may be related to a general mood (e.g., confused, happy, bored) of the user when viewing one or more segments of particular multimedia content.