bnosac/ETM
Topic Modelling in Semantic Embedding Spaces
This tool helps you uncover the main themes within a large collection of text documents. You provide your documents and a list of related words (word embeddings), and it outputs distinct topics, each with a list of its most representative terms. It's designed for researchers, analysts, or content strategists who need to understand the underlying subjects in their textual data.
Use this if you need to automatically identify and categorize the key topics present in a large corpus of text documents, especially when you want to leverage semantic relationships between words.
Not ideal if you're looking for a simple keyword extraction tool or if your dataset is too small to build meaningful word relationships.
Stars
51
Forks
3
Language
R
License
—
Category
Last pushed
Nov 26, 2025
Commits (30d)
0
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