Exact vs Normalised Matching: How Many True Matches Do You Find?
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Lessons in this course
- Normalising Company Names: TRIM, LOWER, SUBSTITUTE and Legal SuffixesFree
- Blocking Keys: First Letter + Postcode to Limit Comparisons Pro
- Exact vs Normalised Matching: How Many True Matches Do You Find? Pro
- Character Bigram Similarity: Jaccard and Dice with MID and SEQUENCE Pro
- Token Overlap for Company Names: Word Jaccard and the Overlap Coefficient Pro
- Combined Match Score: Weights and Two Thresholds (Match, Review, Non-Match) Pro
- Precision and Recall of the Matcher against a Labelled Sample Pro
- De-duplication: Cluster IDs, the Golden Record and the Score Distribution Pro