Text Segmentation

Explore how to apply dynamic programming to the text segmentation problem by recursively partitioning a string into valid words. Understand memoization techniques that eliminate redundant computations, drastically improving efficiency. Learn to develop and implement algorithms that use recursion and bottom-up tabulation to determine if a string can be segmented into a valid sequence of words.

We'll cover the following...

Optimizing the text segmentation problem
Memoization
Developing dynamic programming algorithms
The pitfalls of greedy algorithms
Importance of avoiding a greedy algorithm

Optimizing the text segmentation problem

For our next dynamic programming algorithm, let’s consider the text segmentation problem from the previous chapter. We are given a string $A[1 .. n]$ and a subroutine $IsWord$ that determines whether a given string is a word (whatever that means), and we want to know whether $A$ can be partitioned into a sequence of words.

We solved this problem by defining a function $Splittable(i)$ that returns True if and only if the $suffix\space A[i .. n]$ can be partitioned into a sequence of words. We need to compute $Splittable(1)$ . This function satisfies the recurrence

S p l i t t a b l e (i

1.Getting Started

2.Introduction to Algorithm

3.Recursion

4.Backtracking

5.Dynamic Programming

6.Greedy Algorithms

Assessment

7.Basic Graph Algorithms

8.Depth-First Search

9.Minimum Spanning Trees

10.Shortest Paths

11.All-Pairs Shortest Paths

Assessment

12.Wrapping up

Text Segmentation

Optimizing the text segmentation problem