Topic Modeling in Embedding Spaces
Topic Modeling in Embedding Spaces
About this item
Full title
Author / Creator
Publisher
One Rogers Street, Cambridge, MA 02142-1209, USA: MIT Press
Journal title
Language
English
Formats
Publication information
Publisher
One Rogers Street, Cambridge, MA 02142-1209, USA: MIT Press
Subjects
More information
Scope and Contents
Contents
Topic modeling analyzes documents to learn meaningful patterns of words. However, existing topic models fail to learn interpretable topics when working with large and heavy-tailed vocabularies. To this end, we develop the
(
), a generative model of documents that marries traditional topic models with word embeddings. More specifically, the
Alternative Titles
Full title
Topic Modeling in Embedding Spaces
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_crossref_primary_10_1162_tacl_a_00325
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1162_tacl_a_00325
Other Identifiers
ISSN
2307-387X
E-ISSN
2307-387X
DOI
10.1162/tacl_a_00325
