Previously, I showed you how to create N-Gram frequency tables from large text datasets. Unfortunately, when used on very large datasets such as the English language Wikipedia and Gutenberg corpora, memory limitations limited these scripts to unigrams. Here, I show you how to use the BerkeleyDB database to create N-gram tables of these large datasets.
The Word Frequency Table scripts can be easily expanded to calculate N-Gram frequency tables. This post explains how.
As well as using the Gutenberg Corpus, it is possible to create a word frequency table for the English text of the Wikipedia encyclopedia.
Following on from the previous article about scanning text files for word statistics, I shall extend this to use real large corpora. First we shall use this script to create statistics for the entire Gutenberg English language corpus. Next I shall do the same with the entire English language Wikipedia.
Now that we can segment words and sentences, it is possible to produce word and tuple frequency tables. Here I show you how to create a word frequency table for a large collection of text files.