Email Signature Extraction via Block Scoring and Pattern Matching
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Solution Overview
Problem
Current methods for extracting signature contact information from emails are inefficient and prone to errors, as they require manual identification and are not standardized across different email formats and systems, leading to inefficiencies in populating Customer Relationship Management (CRM) systems.
Innovation Solution
An automated method and system that processes email bodies to identify patterns of predefined signature data, generates block scores based on pattern matches, and selects the most likely block containing signature contact information, such as name, title, email, and phone number, for extraction and storage in CRM systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual identification and extraction of contact information from emails is performed, then flexibility in handling various email formats is maintained, but productivity and accuracy of data entry into CRM systems deteriorate due to time consumption and human errors
Solution Approach 1:
The system performs self-service by automatically identifying and extracting contact information from email bodies without requiring manual intervention. The automated processing scans email content, identifies signature blocks containing contact details, and populates CRM systems directly, eliminating the need for manual data entry while maintaining adaptability to various email formats through pattern recognition algorithms
Solution Approach 2:
The patent replaces the mechanical manual process of identifying and copying contact information with an automated computational system. The system uses pattern matching and text analysis algorithms to automatically locate signature blocks and extract contact details, substituting human manual operations with automated software processing that handles various email formats through predefined patterns
2Adaptability or versatility
If manual data entry from emails to CRM systems is performed, then adaptability to different email formats is maintained, but reliability of stored data deteriorates due to omissions and errors introduced during manual entry
Solution Approach 1:
The system performs self-service by automatically identifying and extracting contact information from email bodies without requiring manual intervention. The automated processing scans email content, identifies signature blocks containing contact details, and populates CRM systems directly, eliminating the need for manual data entry while maintaining adaptability to various email formats through pattern recognition algorithms
Solution Approach 2:
The system creates an accurate copy of contact information directly from the email source to the CRM system through automated extraction. By copying data through automated pattern recognition rather than manual transcription, the system preserves the original accuracy of contact details while adapting to different email formats, thereby eliminating errors introduced during manual copying processes
3Productivity
If automated pattern matching is used to identify signature information, then productivity of data extraction is improved, but device complexity increases due to the need for pattern recognition algorithms
Solution Approach 1:
The patent applies segmentation by dividing the email body into distinct blocks or sections for analysis. Instead of processing the entire email at once, the system segments the content into manageable units such as signature blocks, body text, and headers. This segmentation reduces the complexity of pattern matching by focusing algorithms on specific regions where contact information is likely to appear, thereby maintaining high productivity while managing system complexity
Solution Approach 2:
The system applies local quality by concentrating pattern recognition resources on specific regions of the email where signature information is most likely to be found. Rather than uniformly analyzing the entire email, the algorithm focuses computational effort on identified signature blocks or regions containing contact details, optimizing productivity while reducing overall processing complexity through targeted analysis
4Measurement precision
If the system reviews multiple blocks of email content for pattern matches, then measurement precision of contact information extraction is improved, but loss of time increases due to comprehensive scanning
Solution Approach 1:
The patent applies segmentation by dividing the email body into distinct blocks or sections for analysis. Instead of processing the entire email at once, the system segments the content into manageable units such as signature blocks, body text, and headers. This segmentation reduces the complexity of pattern matching by focusing algorithms on specific regions where contact information is likely to appear, thereby maintaining high productivity while managing system complexity
Solution Approach 2:
The system performs preliminary action by pre-identifying potential signature blocks or regions in the email before conducting detailed pattern matching. By first locating areas where contact information is likely to appear (such as blocks containing email addresses, phone numbers, or signature indicators), the system prepares the data structure in advance, enabling faster and more precise extraction without requiring comprehensive scanning of the entire email content
Data Source
AI summary
An email message body is processed to identify groups of characters that match patterns from a set of predefined signature data patterns. For each identified group of characters, a respective block of the email message body is reviewed to identify other groups of characters within the respective block that also match patterns from the set of predefined signature data patterns. A block score is generated for the respective block based on the groups of characters identified as matching patterns from the set of predefined signature data patterns. One of the blocks is selected based on the block scores generated for the respective blocks, and signature contact information is retrieved from the selected block.