The aim of this project is to use the text from biomedical and life science literature to gain insights on research topic trends over time.
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Updated
Sep 20, 2017 - Jupyter Notebook
The aim of this project is to use the text from biomedical and life science literature to gain insights on research topic trends over time.
This package consists of functionalities for dynamic topic modelling and its visualization
Implementation of the Multilingual Dynamic Topic Model as presented in our paper
Scripts for the MA research about Brazil’s parliamentary discourses dynamics on the Amazon rainforest.
✨ Awesome - A curated list of amazing Topic Models (implementations, libraries, and resources)
2nd place at ACDH virtual Open Data hackathon series 2019: International Open Data Day
Aligned Neural Topic Model (ANTM) for Exploring Evolving Topics: a dynamic neural topic model that uses document embeddings (data2vec) to compute clusters of semantically similar documents at different periods, and aligns document clusters to represent topic evolution.
Automatically extract skills from HTML job ads to understand their relevance over time. Uses Python, translation, NLP, topic modeling and dynamic topic modeling. Three parts: Translation & Preprocessing, Skill Section Extraction, Skill Analysis.
Topic modeling for NYT articles.
한국 현대문학 박사학위 논문 서지 데이터 분석
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