<Trie> 212 <Array> 229

212. Word Search II

class TrieNode{
    char val;
    TrieNode[] children;
    String word;

    public TrieNode(char x){
        children = new TrieNode[26];
        word = null;
    }
}
class Solution {
    public List<String> findWords(char[][] board, String[] words) {
        List<String> res = new ArrayList<>();
        if(board == null || board.length == 0) return res;
        TrieNode root = new TrieNode(' ');
        buildTrie(root, words);
        for(int i = 0; i < board.length; i++){
            for(int j = 0; j < board[0].length; j++){
                char c = board[i][j];
                if(root.children[c - 'a'] != null){
                    dfs(board, i, j, root, res);
                }
            }
        }
        return res;
    }

    private void buildTrie(TrieNode root, String[] words){
        for(String s : words){
            TrieNode cur = root;
            for(char c : s.toCharArray()){
                if(cur.children[c - 'a'] == null){
                    cur.children[c - 'a'] = new TrieNode(c);
                }
                cur = cur.children[c - 'a'];
            }
            cur.word = s;
        }
    }

    private void dfs(char[][] board, int i, int j, TrieNode cur, List<String> res){
        if(i < 0 || i >= board.length || j < 0 || j >= board[0].length) return;

        char c = board[i][j];
        if(c == '*') return;
        if(cur.children[c - 'a'] == null) return;

        cur = cur.children[c - 'a'];
        if(cur.word != null){
            res.add(cur.word);
            cur.word = null;
        }

        board[i][j] = '*';
        dfs(board, i + 1, j, cur, res);
        dfs(board, i - 1, j, cur, res);
        dfs(board, i, j + 1, cur, res);
        dfs(board, i, j - 1, cur, res);
        board[i][j] = c;
    }
}

229. Majority Element II

Boyer-Moore Majority Vote algorithm

这道题让我们求出现次数大于 n/3 的数字，而且限定了时间和空间复杂度，那么就不能排序，也不能使用 HashMap，这么苛刻的限制条件只有一种方法能解了，那就是摩尔投票法 Moore Voting，这种方法在之前那道题Majority Element中也使用了。

1. given n numbers and 1 counter (which is the majority element problem), at most (n/2) times pair-out can happen, which will lead to the survival of the only element that appeared more than n/2 times.
2. given n numbers and 2 counters (which is our case), at most n/3 times of pair-out can happen, which will lead to the survival of elements that appeared more than n/3 times.
3. given n numbers and k counters, at most (n/k+1) times of pair-out can happen, which will lead to the survival of elements that appeared more than n/(k+1) times.

当出现次数超过n/2的数的时候，只需要1个counter, 出现次数超过n/3的时候，需要2个counter，以此类推。

public class Solution {
    public List<Integer> majorityElement(int[] nums) {
        List<Integer> res = new ArrayList<>();
        if(nums.length == 0)
            return res;

        int num1 = nums[0]; int num2 = nums[0]; int count1 = 0; int count2 = 0 ;

        for (int val : nums) {
            if(val == num1)
                count1++;
            else if (val == num2)
                count2++;
            else if (count1 == 0) {
                num1 = val;
                count1++;
                }
            else if (count2 == 0) {
                num2 = val;
                count2++;
            }
            else {
                count1--;
                count2--;
            }
        }
        count1 = 0;
        count2 = 0;
        for(int val : nums) {
            if(val == num1)
                count1++;
            else if(val == num2)
                count2++;
        }
        if(count1 > nums.length/3)
            res.add(num1);
        if(count2 > nums.length/3)
            res.add(num2);
        return res;
    }
}