This article is meant to be a gentle introduction into formal language theory. As with everything, we will try to balance mathematical rigour with concrete examples that have linguistically motivated examples.
Topics to touch on:
Formal languages are defined to have a certain, specific alphabet. The alphabet may be denoted by ∑.
This alphabet set, consists of elements called letters. This set is a finite set. Each letter is a symbol that can be from “abc…”, “123…”. Symbols can even be words.
A sequence of letters may be called a word or a string.
Then these are examples of string:
The length of a string, or the number of characters in a string, is denoted by |w|.
We consider the empty string of 0 length as unique and denote by ϵ.
Concatenation, is the addition of 2 strings together, where order matters. For example, “artificial” + “intelligence” = “artificialintelligence”. Given:
Concatenation is denoted by:
For every string w:
For every string w:
For all exponents n>0:
If w=”go”, then:
If w is a string, then reverse of w is:
Palindrome is defined by:
Here we mean words like “ana”, “anna”, “racecar” etc. I’m not sure if these are technically called symmetry. But everyone would understand exactly what I mean if I called these words symmetric. If there is such a concept as symmetry in formal language theory, I wonder how it would connect to Group Theory.
Coincidentally, group theory arises out of our need to study symmetry of geometrical objects and spaces. Where we might build out the theory exactly the same way that formal language theory is built, using sets as the objects then defining standard operations.
On this later…
If w is a string, then a substring of w is a sequence formed by taking a contiguous symbols of w in the order in which they occur in w.
is a substring of w if and only if there are 2 other substring such that
Also w₁ and wᵣ may be empty strings. These two substring are special cases of substrings called, prefix and suffix.
#naturallanguageprocessing #deep-learning #machine-learning #linguistics #deep learning
Objects, Operations, Regular Expressions and Finite State Automata. This article is meant to be a gentle introduction into formal language theory.