Package Usage: pypi: top2vec

Top2Vec learns jointly embedded topic, document and word vectors.
35 versions
Latest release: over 1 year ago
2 dependent packages
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View more package details: https://packages.ecosystem.code.gouv.fr/registries/pypi.org/packages/top2vec

Dependent Repos 1

equipebd/atem

ATEM is a novel framework for studying topic evolution in scientific archives. It is based on dynamic topic modeling and dynamic graph embedding techniques that explore the dynamics of content and citations of documents within a scientific corpus. ATEM explores a new notion of contextual emergence for the discovery of emerging interdisciplinary research topics based on the dynamics of citation links in topic clusters. Our experiments show that ATEM can efficiently detect emerging cross-disciplinary topics within the DBLP archive of over five million computer science articles.

Last synced: 7 months ago