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KlaraGtknst / text_topic

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This repository implements a pipeline to store various data of files from a large unstructured dataset. These fields are used for topic modeling (wordclouds, based on low-dimensional versions of embedding vectors, Named Entity Clustering and document-topic incidences). The information is aggregated and visualised using FCA.

elasticsearch visualisation embeddings documents ner text-data fca topics-modeling sentence-transformers top2vec topic-aggregation ner-clustering
  • Updated Feb 14, 2025
  • Python

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