# Topic Modeling: Optimizing for Human Interpretability

DevFeed: [Topic Modeling: Optimizing for Human Interpretability](<https://devfeed.tech/articles/topic-modeling-15928.md>)

Original publisher: [Read original article](<https://developer.squareup.com/blog/topic-modeling-optimizing-for-human-interpretability>)

Author: Alyssa Wisdom

Published: 2017-12-20T22:38:24Z

Content type: tutorial

Language: en

Sources: [Square Corner Blog RSS Feed](<https://devfeed.tech/sources/square-corner-blog-rss-feed.md>)

Topics: [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [data](<https://devfeed.tech/topics/data.md>), [information retrieval](<https://devfeed.tech/topics/information-retrieval.md>), [tokenization](<https://devfeed.tech/topics/tokenization.md>)

Tags: [article](<https://devfeed.tech/tags/article.md>), [clustering](<https://devfeed.tech/tags/clustering.md>), [data](<https://devfeed.tech/tags/data.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [tokenization](<https://devfeed.tech/tags/tokenization.md>)

## AI overview

This article explains topic modeling as an unsupervised machine-learning method for identifying latent topics in large text collections. It discusses evaluating topic models, improving interpretability, preprocessing text, choosing the number of topics, and using document-term matrices.

## Source excerpt

Optimizing for Human Interpretability