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feat: improve name detection with intelligent number stripping #520
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Enhanced the name detection algorithm to be more robust and smarter when handling numbers and special characters in email addresses. The algorithm now intelligently strips numbers from names while preserving valid name parts. Key improvements: - Intelligently strips numbers from patterns like "john1.due2" → "John Due" - Multiple cleaning strategies: removes all numbers, trailing numbers, or leading numbers based on context - Smart fallback logic: keeps original when stripping would result in too-short names - Correctly handles reserved words (admin, support, etc.) even after number stripping - Maintains backward compatibility with confidence scoring Examples: - john1.due2@example.com → John Due (85% confidence) - mary123.smith456@example.com → Mary Smith (85% confidence) - 2john.smith@example.com → John Smith (85% confidence) - a1.b2@example.com → A1 B2 (keeps original as cleaned would be too short) All 164 tests pass with no regressions.
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Summary
john1.due2@example.com→ "John Due" instead of "John1 Due2"Changes
Core Algorithm Improvements
Intelligent number stripping: Multiple strategies for cleaning names
a1.b2stays as is sinceaandbare too short)Smart validation: Correctly handles reserved words like "admin", "support" even after number stripping
Enhanced confidence scoring: Adjusted confidence levels based on cleaning success
Examples of Improved Parsing
john1.due2@example.commary123.smith456@example.com2john.smith@example.comdev3.ops4@example.comtest1.user2@example.coma1.b2@example.comTest Plan
Breaking Changes
None - this is a backward-compatible enhancement that improves name detection accuracy while maintaining the same API.