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hierarchical-taxonomy-clustering

Build unified multi-level category taxonomy from hierarchical product category paths from any e-commerce companies using embedding-based recursive clustering with intelligent category naming via weighted word frequency analysis.

tasks-extra/taxonomy-tree-merge/environment/skills/hierarchical-taxonomy-clustering/SKILL.md

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# Hierarchical Taxonomy Clustering

Create a unified multi-level taxonomy from hierarchical category paths by clustering similar paths and automatically generating meaningful category names.

## Problem

Given category paths from multiple sources (e.g., "electronics -> computers -> laptops"), create a unified taxonomy that groups similar paths across sources, generates meaningful category names, and produces a clean N-level hierarchy (typically 5 levels). The unified category taxonomy could be used to do analysis or metric tracking on products from different platform.

## Methodology

1. **Hierarchical Weighting**: Convert paths to embeddings with exponentially decaying weights (Level i gets weight 0.6^(i-1)) to signify the importance of category granularity
2. **Recursive Clustering**: Hierarchically cluster at each level (10-20 clusters at L1, 3-20 at L2-L5) using cosine distance
3. **Intelligent Naming**: Generate category names via weighted word frequency + lemmatization + bundle word logic
4. **Quality Control**: Exclude all ancestor words (parent, grandparent, etc.), avoid ancestor path duplicates, clean special characters