# naive bayes

Published articles for naive bayes.

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## Word Segmentation with Google's N-Gram Corpus

DevFeed: [Word Segmentation with Google's N-Gram Corpus](<https://devfeed.tech/articles/word-segmentation-or-makingsenseofthis-40255.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2012/01/15/word-segmentation/>)

Published: 2012-01-15T11:10:51Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Programming](<https://devfeed.tech/topics/programming.md>), [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Google](<https://devfeed.tech/topics/google.md>), [Code](<https://devfeed.tech/topics/code.md>), [Python](<https://devfeed.tech/topics/python.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [article](<https://devfeed.tech/tags/article.md>), [code](<https://devfeed.tech/tags/code.md>), [dynamic-programming](<https://devfeed.tech/tags/dynamic-programming.md>), [google](<https://devfeed.tech/tags/google.md>), [linguistics](<https://devfeed.tech/tags/linguistics.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [naive-bayes](<https://devfeed.tech/tags/naive-bayes.md>), [ngrams](<https://devfeed.tech/tags/ngrams.md>), [programming](<https://devfeed.tech/tags/programming.md>), [python](<https://devfeed.tech/tags/python.md>)

### AI overview

This tutorial explains word segmentation, counts the exponentially many possible segmentations, and introduces a dynamic-programming approach using a simple model based on a subset of Google's n-gram corpus.

### Source excerpt

A First Look at Google's N-Gram Corpus In this post we will focus on the problem of finding the appropriate word boundaries in strings like "homebuiltairplanes", as is common in web URLs like www.homebuiltairplanes.com. This is an interesting problem because humans do it so easily, but there is no obvious programmatic solution. We will begin this article by addressing the complexity of this problem, continue by implementing a simple model using a subset of Google's n-gram corpus, and finish by describing our future plans to enhance the model.