Reades, Jonathan;
Williams, Jennie;
(2023)
Clustering and Visualising Documents using Word Embeddings.
Programming Historian
, 12
(2023)
10.46430/phen0111.
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Abstract
This lesson uses word embeddings and clustering algorithms in Python to identify groups of similar documents in a corpus of approximately 9,000 academic abstracts. It will teach you the basics of dimensionality reduction for extracting structure from a large corpus and how to evaluate your results.
| Type: | Article |
|---|---|
| Title: | Clustering and Visualising Documents using Word Embeddings |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.46430/phen0111 |
| Publisher version: | https://doi.org/10.46430/phen0111 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10218058 |
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