Email Content Hashing for Cross-Server Grouping
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Solution Overview
Problem
Existing methods for relating and grouping emails, such as text searches and server-assigned metadata, are inefficient for large volumes and fail to capture emails with copied content without forwarding or replying, and are server-specific, limiting their transference across multiple servers.
Innovation Solution
A method that processes email text to determine boundaries like headers, signatures, and bodies, generates hashes for these sections, and uses these hashes to trace and group emails based on content, independent of server-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text searches and server-assigned metadata are used to relate and group emails, then emails can be organized and retrieved, but the method becomes inefficient for large volumes and fails to capture emails with copied content without forwarding or replying
Solution Approach 1:
The patent uses hash values as digital copies or fingerprints of email content. Instead of comparing entire email texts, the system generates hash values from email bodies and compares these compact representations. This allows efficient identification of emails with copied content even when not forwarded or replied to, resolving the contradiction between efficiency and detection accuracy.
Solution Approach 2:
The patent replaces traditional text-based search and metadata assignment mechanisms with a hash-based content comparison system. By substituting the mechanical text comparison process with cryptographic hash function evaluation, the system achieves both high efficiency for large volumes and high reliability for detecting content relationships.
2Adaptability or versatility
If server-specific metadata is used to organize emails, then emails can be grouped within a single server, but the method is not transferable across multiple servers
Solution Approach 1:
The patent creates a universal email grouping mechanism that works across multiple servers by using hash values of email content rather than server-specific metadata. The hash-based approach is server-agnostic, allowing the same grouping logic to be applied universally across different email systems without requiring server-specific adaptations, thus achieving cross-server versatility.
Solution Approach 2:
The patent extracts the essential identifying feature of emails (their content hash) separate from server-specific metadata. By taking out the content-based hash value as the primary grouping key, the system eliminates dependence on server-specific data structures and makes the grouping mechanism transferable across different email servers.
3Reliability
If traditional email tracing methods are used, then forwarded or replied emails can be identified, but emails with copied content that are not forwarded or replied to are not captured
Solution Approach 1:
The patent uses hash values to detect content copying between emails. By comparing hash values of email bodies, the system can identify emails that contain copied content even when the traditional forward or reply functionality was not used. This expands the quantity of related emails identified while maintaining high detection accuracy through reliable hash comparison.
Data Source
AI summary
Examples described herein include receiving text of an email, determining a header of an email message in the email, and determining a body of the email message. Examples also include modifying the text of the email to indicate a beginning boundary and an ending boundary of the header, modifying the text of the email to indicate a beginning boundary and an ending boundary of the body, generating a hash of the header, generating a hash of the body, and tracing the email based on the hash of the header.