Transitive Clustering

Explore transitive clustering in entity resolution, learning how this fast, conflict-free method enhances recall yet can reduce precision. Understand its operation through graphs, connected components, and real-world examples to balance classification accuracy.

We'll cover the following...

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Precision and recall
Resolving restaurants
Key takeaway

Transitive clustering is the mother of all clustering algorithms for entity resolution. Its logic is appealing, super fast to compute, and beneficial for recall. However, it is typically paid with a significant reduction in precision. Let’s begin by examining how the algorithm works on a small dataset.

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Clustering follows pairwise prediction. Let $r_1,\ldots,r_n$ denote the original records, where $c_{ij}=1$ if the pairwise model predicts a match between $r_i$ ...

1.Introduction to Entity Resolution and Applications

2.A Quickstart Guide Using the RecordLinkage Package

3.Preprocessing

4.Indexing

5.Feature Engineering

6.Pairwise Matching

7.Clustering

8.Integration

Assessment

Mini Project

9.Conclusion

10.Appendix

Project

Transitive Clustering

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