Given a string s and a dictionary of words dict, add spaces in s to construct a sentence where each word is a valid dictionary word.
Return all such possible sentences.
For example, given
s = "catsanddog"
,
dict = ["cat", "cats", "and", "sand", "dog"]
.
A solution is ["cats and dog", "cat sand dog"]
.
public class Solution { public List<String> wordBreak(String s, Set<String> dict) { List<String> res = new ArrayList<String>(); if(s.length() == 0 || s == null) return res; recursive(s, 0, dict, "", res); return res; } public void recursive(String s, int index, Set<String> dict, String string, List<String> res){ if(index >= s.length()){ res.add(string); return; } StringBuilder builder = new StringBuilder(); for(int i = index; i < s.length(); i++){ builder.append(s.charAt(i)); if(dict.contains(builder.toString())){ String str = string.isEmpty() ? builder.toString() : (string + " " + builder.toString()); recursive(s, i + 1, dict, str, res); } } } }
大数据集是通不过的。网上看到了一个剪枝的办法,就是利用DP的思想,如果某个点i在之前的搜索中没有得到结果,那么以后就不进行搜索了。
public class Solution { public List<String> wordBreak(String s, Set<String> dict) { List<String> res = new ArrayList<String>(); if(s.length() == 0 || s == null) return res; boolean[] possible = new boolean[s.length() + 1]; Arrays.fill(possible, true); recursive(s, 0, dict, "", res, possible); return res; } public void recursive(String s, int index, Set<String> dict, String string, List<String> res, boolean[] possible){ if(index >= s.length()){ res.add(string); return; } StringBuilder builder = new StringBuilder(); for(int i = index; i < s.length(); i++){ builder.append(s.charAt(i)); //only perform search if there are possible solutions in level i + 1 if(dict.contains(builder.toString()) && possible[i + 1]){ String str = string.isEmpty() ? builder.toString() : (string + " " + builder.toString()); int beforeSearch = res.size(); recursive(s, i + 1, dict, str, res, possible); //if the result size is not changed after the search, then there is no solution at i if(beforeSearch == res.size()) possible[i + 1] = false; } } } }