Cognitive Learning Framework for Dark Data Processing
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Solution Overview
Problem
Current technologies face challenges in efficiently processing and analyzing large volumes of complex data, particularly 'dark data,' which is often neglected or underutilized, making it difficult to extract actionable insights.
Innovation Solution
A cognitive learning method and system that processes data from multiple sources using a cognitive inference and learning system, implementing cognitive learning techniques within a cognitive learning framework to generate insights and update destinations accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data processing approaches are used to handle big data, then data processing can be performed with simple tools, but the processing efficiency is insufficient and cannot handle large volumes of complex data within tolerable time intervals
Solution Approach 1:
The patent segments the data processing task into multiple cognitive operations including data collection from diverse sources, data preparation, cognitive inference, learning, and validation. Each segment is handled by specialized cognitive computing components that work in parallel, improving overall processing efficiency while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces cognitive computing systems as intermediary layers between traditional data processing tools and big data. These cognitive systems include cognitive agents, knowledge graphs, and inference engines that mediate the processing of complex data, enabling efficient handling of dark data and unstructured information that traditional tools cannot process effectively.
2Loss of information
If dark data is collected and stored for potential insights, then valuable information becomes available, but the data becomes difficult to access, process, and utilize at the right time and place
Solution Approach 1:
The patent applies preliminary action by pre-processing dark data through cognitive inference and learning operations before it is needed. Cognitive agents continuously analyze and interpret dark data in the background, preparing actionable insights in advance. This allows the system to quickly access and utilize pre-processed insights when needed, rather than processing raw dark data at the moment of need.
Solution Approach 2:
The patent implements feedback mechanisms where cognitive learning results are continuously validated and used to improve future data processing. The system learns from the utilization patterns of dark data and adjusts its processing strategies, making previously inaccessible dark data progressively easier to access and utilize through iterative improvement.
Data Source
AI summary
A cognitive learning method comprising: receiving data from a plurality of data sources; processing the data from the plurality of data sources to perform a cognitive learning operation, the processing being performed via a cognitive inference and learning system, the cognitive learning operation implementing a cognitive learning technique according to a cognitive learning framework, the cognitive learning operation applying the cognitive learning technique to generate a cognitive learning result; and, updating a destination based upon the learning result.