Abstract
In the previous chapters, we covered several techniques to analyze text and extract interesting insights. We looked at supervised machine learning techniques, which are used to categorize text documents into several assumed categories. Unsupervised techniques like topic models and document summarization were also covered, which involved trying to retrieve key themes and information from large text documents and corpora.
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© 2019 Dipanjan Sarkar
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Sarkar, D. (2019). Text Similarity and Clustering. In: Text Analytics with Python. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4354-1_7
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DOI: https://doi.org/10.1007/978-1-4842-4354-1_7
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4353-4
Online ISBN: 978-1-4842-4354-1
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