md-experiments/picture_text
Interactive tree-maps with SBERT & Hierarchical Clustering (HAC)
This tool helps you quickly understand large collections of short text documents, like news headlines or social media posts. It takes your list of texts and automatically organizes them into semantically related groups, presenting them as an interactive treemap. Anyone needing to find patterns and topics within many short texts can use this to explore and filter information easily.
No commits in the last 6 months. Available on PyPI.
Use this if you need to visually categorize and explore themes within a large set of short, general-purpose text documents without extensive manual effort.
Not ideal if your documents are very long, highly technical, or require extremely nuanced domain-specific categorization.
Stars
30
Forks
9
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 31, 2024
Commits (30d)
0
Dependencies
8
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/md-experiments/picture_text"
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