Natural Language Processing (Part 40)-Autocorrect
📚Chapter5: Autocorrect and Mininum Edit Distance
Introduction
I’ll give you a brief overview of autocorrect and how it works. You will learn to identify misspelled words. What is an additive distance, and how to calculate probabilities of the correct word.
Sections
What is autocorrect.
How to autocorrect works.
Summary
Section 1- What is autocorrect.
Let’s get started with a simple definition. What is autocorrect? Autocorrect is an application that changes misspelled words into the correct ones. You probably know it very well already. You have it on your phone, tablet, and on your computer inside your document editors and email applications.
For example, it takes a sentence like this one, happy birthday deah friend, and corrects the misspelled word, deah, to a word that you probably intended to write, which in this context would be dear, correctly spelled D-E-A-R. But what if you typed deer instead of dear?
Here, you see the word is spelled correctly, but it’s context is incorrect. Well, unless your friend happens to be an actual deer, you will not test for this contextual error this week. As it’s a more sophisticated problem, you’ll get to learn
about that another time. Instead, this week you will only look for words that have been misspelled and make corrections to these. This involves a simple, it’s powerful model, as you will see. Let me show you an overview of how autocorrect works.
Section 2- How to autocorrect works.
There are four key steps. First, identify an incorrect word. Misspelling is one way to do this. Second, find strings 1, 2, 3 or n edit distances away. Don’t worry, you will learn about minimum edit
distance shortly.
For now, what’s important to know is that, if a string is one edit distance away from the string that you typed, it’s more similar to your string compared to a string that is two edit distances away.
Third, filter the strings for real words that are spelled correctly.
Fourth, calculate word probabilities, which tell you how likely each word is to appear in this context and choose the most likely candidate to be the replacement.
Summary
Now you have a better intuition for what is autocorrect and how it works. That’s good. Next you’ll take a closer look at the details for implementing each step so that you can begin to build the autocorrects model. Now you know how autocorrect works.
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Natural Language Processing with Probabilistic models
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To Do List
1- Collects Keys points from the blogs
Source
1- Natural Language Processing with Probabilistic Models (Coursera)
