Non-linear Packet Delay Distribution for Social Media Intelligence
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for monitoring social media data struggle to extract actionable intelligence in real-time, often producing excessive data that includes irrelevant information, making it difficult for businesses to identify valuable insights effectively.
Innovation Solution
A method and system that utilize a computer system with multiple processors to identify high-value information in data streams by combining classification models within mission definitions, distributing packets to executable mission definitions, and executing these models in parallel to filter and classify data streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional tools and methods are used to monitor social media data, then data collection is performed, but the output contains excessive irrelevant information and fails to extract actionable intelligence
Solution Approach 1:
The patent extracts only the valuable subset of information from the data stream by using classification models that identify and extract high-value packets (containing actionable intelligence) while discarding irrelevant data. This is achieved through mission definitions that specify criteria for extracting only the most valuable information from social media streams.
Solution Approach 2:
The patent applies different classification criteria and processing approaches to different portions of the data stream based on their value and relevance. High-value packets are identified and processed differently from low-value packets, with the system adapting its processing intensity and methods to the local characteristics of each data packet.
2Measurement precision
If multiple classification models are combined to identify high-value information, then information extraction accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the classification task into multiple independent classification models that can be combined in series. Each model focuses on specific aspects of high-value information identification, and their results are combined to achieve high overall accuracy. This segmentation allows the system to manage complexity by breaking down the overall classification task into smaller, more manageable components.
Solution Approach 2:
The patent combines multiple classification models in series within mission definitions to achieve high accuracy in identifying high-value information. The models are merged such that their combined output provides more accurate classification than any single model alone, while the system manages this complexity through structured mission definition frameworks.
3Productivity
If data packets are distributed to multiple executable mission definitions for parallel execution, then processing speed is improved, but non-linear delay occurs in packet delivery
Solution Approach 1:
The patent implements dynamic load balancing that adapts the distribution of data packets to executable mission definitions based on current system conditions, processing loads, and packet characteristics. This dynamic approach allows the system to optimize processing speed while minimizing delays by adjusting packet routing in real-time based on changing conditions.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor the performance and status of executable mission definitions, using this information to adjust packet distribution dynamically. The system receives feedback on processing delays and performance metrics, then adjusts its packet routing and distribution strategy to minimize non-linear delays while maintaining high processing throughput.
Data Source
AI summary
A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.