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AI Features

Candidate Model

Explore how candidate models generate correction suggestions for misspelled words by applying edit operations like deletions, transpositions, replacements, and insertions. Understand the use of edit distance-based filtering to manage candidate sets, and gain hands-on experience implementing functions for generating one or two edits away candidate words and validating them within a dictionary for effective spellchecking.

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What is a candidate model?

A candidate model is a model that generates a list of possible corrections for a given misspelled word. We can represent this with ccandidatesc ∈ \text{candidates}. The goal of a candidate model is to provide a set of suggestions for us to choose from when correcting a spelling mistake.

There are various approaches to building a candidate model for a spellchecker, but they typically involve applying a set of edit operations to the misspelled word to generate a set of candidate corrections. Some of the most common methods include:

  1. Edit distance models: These models generate a list of possible corrections by applying a series of edit operations to the misspelled word and comparing the resulting words to a dictionary. The algorithm selects the correction with ...