Online Information Verification System Using Author Identity Normalization
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Solution Overview
Problem
The challenge lies in acquiring and verifying credible online information, as existing systems fail to effectively filter out fake and unverifiable content, particularly in online search engines and electronic commerce platforms, where reviews are often unverified and lack credibility, leading to potential misselection of services or products.
Innovation Solution
A system and method that acquire and verify information by normalizing data from various sources, determining the identity of the author, classifying the data based on metadata, and storing it in a structured format, utilizing machine-to-machine communication and closed-loop review mechanisms to ensure credibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from multiple online sources is collected and aggregated, then the quantity and variety of information increases, but the credibility and reliability of the information decreases due to inclusion of unverified content
Solution Approach 1:
The patent segments the information verification process into distinct components: data acquisition from multiple sources, normalization processing, author identity determination, metadata extraction, and classification. This segmentation allows each component to be optimized independently, enabling the system to process large quantities of data while maintaining reliability through structured verification at each stage.
Solution Approach 2:
The patent introduces an intermediary verification layer between raw data collection and final information delivery. This intermediary system normalizes data from various sources, determines author identities, extracts metadata, and classifies information before presenting it to users. This intermediary processing layer filters unverified content while preserving the benefits of multi-source data aggregation.
2Ease of operation
If traditional review systems allow user-submitted reviews without verification, then the ease of operation and user participation increases, but the reliability of reviews decreases due to potential fake reviews
Solution Approach 1:
The patent performs preliminary verification actions before reviews are published. The system determines author identities, normalizes review data, extracts metadata, and classifies reviews according to verified criteria. This preliminary processing ensures that only verified, credible reviews are made visible to users, while maintaining ease of operation through automated background verification processes.
3Reliability
If a system verifies and normalizes data from multiple sources, then the reliability and credibility of information improves, but the device complexity and processing requirements increase
Solution Approach 1:
The patent implements a universal data processing framework that handles multiple data sources, formats, and verification requirements through a single integrated system. The normalization module, identity determination system, metadata extraction process, and classification mechanism work together as a multi-functional platform that can process diverse information types without requiring separate specialized systems for each data source.
4Adaptability or versatility
If online platforms aggregate reviews from multiple sources without centralized verification, then the adaptability and coverage of review data increases, but the loss of information quality occurs due to unverified and inconsistent data
Solution Approach 1:
The patent implements feedback mechanisms where the verification and classification results are used to improve future data processing. The system learns from verified author identities, metadata patterns, and classification outcomes to enhance its verification capabilities. This feedback loop maintains high information quality across diverse data sources by continuously refining the verification process based on accumulated experience.
Data Source
AI summary
A system and method of acquiring and verifying information is provided. The system comprises a processor, and a memory comprising a sequence of instructions which when executed by the processor configure the processor to perform the method. The method comprises acquiring data from a data source associated with an author of the data, normalizing the acquired data, determining, by the processor, an identity of the author of the data, classifying the normalized data based on the identity and acquired metadata, and storing in a memory the normalized data. Normalizing the acquired data comprises parsing the acquired data for meaningful information, extracting metadata from the acquired data, and mapping the parsed information to internal data structures.