Clustering & issue review
Engineering note · Part 8
Constrained Hierarchical Clustering for Email Evidence
How complete-link candidates and contextual constraints can reduce misleading issue merges.
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Clustering & issue review
Candidate groups, distinct requests, broad families and reversible decisions.
Clustering & issue review
Engineering note · Part 9
Why Twelve Categories Do Not Mean Twelve Clusters
Keep broad navigation families separate from the number of concrete issues in a case.
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Engineering note · Part 10
Preventing False Merges: When Similar Emails Describe Different Requests
Why request references, dates and missing context must constrain semantic grouping.
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Engineering note · Part 13
Designing AI Suggestions That Users Can Review and Reverse
How proposal, apply and restore stages keep AI organisation changes understandable and recoverable.
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Engineering note · Part 14
The 69-Item Test That Exposed a Workflow Dead End
What a synthetic consolidation fixture revealed about bounded AI output, unassigned evidence and active issue visibility.
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Experiment design · Part 21
K-Means, DBSCAN and Hierarchical Clustering: Which Fits Evidence Organisation?
Compare clustering assumptions against the actual cost of merging or separating case evidence.
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Experiment design · Part 22
Could Gaussian Mixture Models Represent Ambiguous Evidence Groups?
Explore soft cluster membership without mistaking model responsibilities for evidence certainty.
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