题目描述
给你两个单词 word1
和 word2
, 请返回将 word1
转换成 word2
所使用的最少操作数 。
你可以对一个单词进行如下三种操作:
示例 1:
输入:word1 = "horse", word2 = "ros"
输出:3
解释:
horse -> rorse (将 'h' 替换为 'r')
rorse -> rose (删除 'r')
rose -> ros (删除 'e')
示例 2:
输入:word1 = "intention", word2 = "execution"
输出:5
解释:
intention -> inention (删除 't')
inention -> enention (将 'i' 替换为 'e')
enention -> exention (将 'n' 替换为 'x')
exention -> exection (将 'n' 替换为 'c')
exection -> execution (插入 'u')
提示:
0 <= word1.length, word2.length <= 500
word1
和 word2
由小写英文字母组成
解法
方法一:动态规划
我们定义 $f[i][j]$ 表示将 $word1$ 的前 $i$ 个字符转换成 $word2$ 的前 $j$ 个字符所使用的最少操作数。初始时 $f[i][0] = i$, $f[0][j] = j$。其中 $i \in [1, m], j \in [0, n]$。
考虑 $f[i][j]$:
- 如果 $word1[i - 1] = word2[j - 1]$,那么我们只需要考虑将 $word1$ 的前 $i - 1$ 个字符转换成 $word2$ 的前 $j - 1$ 个字符所使用的最少操作数,因此 $f[i][j] = f[i - 1][j - 1]$;
- 否则,我们可以考虑插入、删除、替换操作,那么 $f[i][j] = \min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1$。
综上,我们可以得到状态转移方程:
$$
f[i][j] = \begin{cases}
i, & \textit{if } j = 0 \
j, & \textit{if } i = 0 \
f[i - 1][j - 1], & \textit{if } word1[i - 1] = word2[j - 1] \
\min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1, & \textit{otherwise}
\end{cases}
$$
最后,我们返回 $f[m][n]$ 即可。
时间复杂度 $O(m \times n)$,空间复杂度 $O(m \times n)$。其中 $m$ 和 $n$ 分别是 $word1$ 和 $word2$ 的长度。
1
2
3
4
5
6
7
8
9
10
11
12
13
14 | class Solution:
def minDistance(self, word1: str, word2: str) -> int:
m, n = len(word1), len(word2)
f = [[0] * (n + 1) for _ in range(m + 1)]
for j in range(1, n + 1):
f[0][j] = j
for i, a in enumerate(word1, 1):
f[i][0] = i
for j, b in enumerate(word2, 1):
if a == b:
f[i][j] = f[i - 1][j - 1]
else:
f[i][j] = min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1
return f[m][n]
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20 | class Solution {
public int minDistance(String word1, String word2) {
int m = word1.length(), n = word2.length();
int[][] f = new int[m + 1][n + 1];
for (int j = 1; j <= n; ++j) {
f[0][j] = j;
}
for (int i = 1; i <= m; ++i) {
f[i][0] = i;
for (int j = 1; j <= n; ++j) {
if (word1.charAt(i - 1) == word2.charAt(j - 1)) {
f[i][j] = f[i - 1][j - 1];
} else {
f[i][j] = Math.min(f[i - 1][j], Math.min(f[i][j - 1], f[i - 1][j - 1])) + 1;
}
}
}
return f[m][n];
}
}
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21 | class Solution {
public:
int minDistance(string word1, string word2) {
int m = word1.size(), n = word2.size();
int f[m + 1][n + 1];
for (int j = 0; j <= n; ++j) {
f[0][j] = j;
}
for (int i = 1; i <= m; ++i) {
f[i][0] = i;
for (int j = 1; j <= n; ++j) {
if (word1[i - 1] == word2[j - 1]) {
f[i][j] = f[i - 1][j - 1];
} else {
f[i][j] = min({f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]}) + 1;
}
}
}
return f[m][n];
}
};
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21 | func minDistance(word1 string, word2 string) int {
m, n := len(word1), len(word2)
f := make([][]int, m+1)
for i := range f {
f[i] = make([]int, n+1)
}
for j := 1; j <= n; j++ {
f[0][j] = j
}
for i := 1; i <= m; i++ {
f[i][0] = i
for j := 1; j <= n; j++ {
if word1[i-1] == word2[j-1] {
f[i][j] = f[i-1][j-1]
} else {
f[i][j] = min(f[i-1][j], min(f[i][j-1], f[i-1][j-1])) + 1
}
}
}
return f[m][n]
}
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21 | function minDistance(word1: string, word2: string): number {
const m = word1.length;
const n = word2.length;
const f: number[][] = Array(m + 1)
.fill(0)
.map(() => Array(n + 1).fill(0));
for (let j = 1; j <= n; ++j) {
f[0][j] = j;
}
for (let i = 1; i <= m; ++i) {
f[i][0] = i;
for (let j = 1; j <= n; ++j) {
if (word1[i - 1] === word2[j - 1]) {
f[i][j] = f[i - 1][j - 1];
} else {
f[i][j] = Math.min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1;
}
}
}
return f[m][n];
}
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26 | /**
* @param {string} word1
* @param {string} word2
* @return {number}
*/
var minDistance = function (word1, word2) {
const m = word1.length;
const n = word2.length;
const f = Array(m + 1)
.fill(0)
.map(() => Array(n + 1).fill(0));
for (let j = 1; j <= n; ++j) {
f[0][j] = j;
}
for (let i = 1; i <= m; ++i) {
f[i][0] = i;
for (let j = 1; j <= n; ++j) {
if (word1[i - 1] === word2[j - 1]) {
f[i][j] = f[i - 1][j - 1];
} else {
f[i][j] = Math.min(f[i - 1][j], f[i][j - 1], f[i - 1][j - 1]) + 1;
}
}
}
return f[m][n];
};
|