Given an input string and a dictionary of words, find out if the input string can be segmented into a space-separated sequence of dictionary words. See following examples for more details.
This is a famous Google interview question, also being asked by many other companies now a days.
Consider the following dictionary
{ i, like, sam, sung, samsung, mobile, ice,
cream, icecream, man, go, mango}
Input: ilike
Output: Yes
The string can be segmented as "i like".
Input: ilikesamsung
Output: Yes
The string can be segmented as "i like samsung" or "i like sam sung".
Recursive implementation:
The idea is simple, we consider each prefix and search it in dictionary. If the prefix is present in dictionary, we recur for rest of the string (or suffix). If the recursive call for suffix returns true, we return true, otherwise we try next prefix. If we have tried all prefixes and none of them resulted in a solution, we return false.
经典DFS题目,把DFS改成DP能减少运算量
package DP;
import java.util.ArrayList;
public class WordBreak {
public static void main(String[] args) {
System.out.println(wordBreakRec("ilikesamsung"));
System.out.println(wordBreakDP("ilikesamsung"));
wordBreakPrintAll("ilikesamsung");
System.out.println(wordBreakRec("samsungandmango"));
System.out.println(wordBreakDP("samsungandmango"));
wordBreakPrintAll("samsungandmango");
System.out.println(wordBreakRec("samsungandmangok"));
System.out.println(wordBreakDP("samsungandmangok"));
wordBreakPrintAll("samsungandmangok");
}
public static boolean wordBreakRec(String s){
int len = s.length();
if(len == 0){
return true;
}
// DFS
// Try all prefixes of lengths from 1 to size
for(int i=1; i<=len; i++){
// The parameter for dictionaryContains is s.substring(0, i)
// s.substring(0, i) which is prefix (of input string) of
// length 'i'. We first check whether current prefix is in
// dictionary. Then we recursively check for remaining string
// s.substring(i) which is suffix of length size-i
if(dictionaryContains(s.substring(0, i)) && wordBreakRec(s.substring(i))){
return true;
}
}
// If we have tried all prefixes and none of them worked
return false;
}
// 打印出所有组合,因为要打印出所有组合而不只是判断能否,所以只能用dfs
public static void wordBreakPrintAll(String s){
ArrayList<String> al = new ArrayList<String>();
wordBreakRec2(s, al);
}
public static void wordBreakRec2(String s, ArrayList<String> al){
int len = s.length();
if(len == 0){
System.out.println(al);
return;
}
// DFS
for(int i=1; i<=len; i++){
String substr = s.substring(0, i);
if(dictionaryContains(substr)){
al.add(substr);
wordBreakRec2(s.substring(i), al);
al.remove(al.size()-1);
}
}
}
private static boolean dictionaryContains(String word){
String[] dict = {"mobile","samsung","sam","sung","man","mango",
"icecream","and","go","i","like","ice","cream"};
for(int i=0; i<dict.length; i++){
if(dict[i].equals(word)){
return true;
}
}
return false;
}
// Returns true if string can be segmented into space separated
// words, otherwise returns false
public static boolean wordBreakDP(String s){
int len = s.length();
if(len == 0){
return true;
}
// Create the DP table to store results of subproblems. The value wb[i]
// will be true if s[0..i-1] can be segmented into dictionary words,
// otherwise false.
boolean[] wb = new boolean[len+1];
for(int i=1; i<=len; i++){
// if wb[i] is false, then check if current prefix can make it true.
// Current prefix is "s.substring(0, i)"
if(wb[i]==false && dictionaryContains(s.substring(0, i))){
wb[i] = true;
}
// wb[i] is true, then check for all substrings starting from
// (i+1)th character and store their results.
if(wb[i] == true){
if(i == len){ // If we reached the last prefix
return true;
}
for(int j=i+1; j<=len; j++){
// Update wb[j] if it is false and can be updated
// Note the parameter passed to dictionaryContains() is
// substring starting from index 'i' to index 'j-1'
if(wb[j]==false && dictionaryContains(s.substring(i, j))){
wb[j] = true;
}
if(j==len && wb[j]==true){ // If we reached the last character
return true;
}
}
}
}
// for(int i=1; i<=len; i++){
// System.out.print(wb[i] + " ");
// }
// If we have tried all prefixes and none of them worked
return false;
}
}
http://www.geeksforgeeks.org/dynamic-programming-set-32-word-break-problem/

本文深入探讨了使用动态规划解决字符串分割问题的算法,通过递归实现和改进为动态规划方法,显著减少了计算量。文章详细解释了如何通过检查前缀是否在字典中以及对剩余字符串进行递归调用来判断原始字符串是否可以被分割成字典中的单词。同时,提供了代码示例和多种输入情况的解析,帮助读者理解算法的实现细节。
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