Given an input string (s) and a pattern (p), implement wildcard pattern matching with support for '?' and '*'.
'?' Matches any single character.
'*' Matches any sequence of characters (including the empty sequence).
The matching should cover the entire input string (not partial).
Note:
scould be empty and contains only lowercase lettersa-z.pcould be empty and contains only lowercase lettersa-z, and characters like?or*.
Example 1:
Input:
s = "aa"
p = "a"
Output: false
Explanation: "a" does not match the entire string "aa".
Example 2:
Input:
s = "aa"
p = "*"
Output: true
Explanation: '*' matches any sequence.
Example 3:
Input:
s = "cb"
p = "?a"
Output: false
Explanation: '?' matches 'c', but the second letter is 'a', which does not match 'b'.
Example 4:
Input:
s = "adceb"
p = "*a*b"
Output: true
Explanation: The first '*' matches the empty sequence, while the second '*' matches the substring "dce".
Example 5:
Input:
s = "acdcb"
p = "a*c?b"
Output: false
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Greedy Solution:
1. There is no need to refresh the status of star, staremerge. Only one star is enough, because the character(for example, 'a') always needs to match some 'a' in s. Matching the former 'a' is better than the latter 'a' in s as is illustrated in the figure. I.e., there is no need to record the matching range for every '*', the latest '*' has the largest range of choice.

2. sbegin is refreshed when mismatch occurs and pbegin is refreshed when meeting new '*';
3. Focusing on s is better than handling the two strings at the same time.
So the final concise code is like:
class Solution:
def isMatch(self, s, p):
slen, plen, i, j = len(s), len(p), 0, 0
star = False
while (i < slen):
if (j < plen and (s[i] == p[j] or p[j] == '?')):
i += 1
j += 1
elif (j < plen and p[j] == '*'):
star_begin_s = i
star_begin_p = j+1
j += 1
star = True
elif (star):
j = star_begin_p
star_begin_s += 1
i = star_begin_s
else:
return False
while (j < plen and p[j] == '*'):
j += 1
if (j == plen):
return True
return False
Using DP, the codes look like:
class Solution {
public:
bool isMatch(const char *s, const char *p) {
int slen = strlen(s), plen = strlen(p), i, j, countp = 0;
for (const char *ptr = p; *ptr; ++ptr)
if (*ptr != '*')
++countp;
if (countp > slen)
return false;
bool dp[500][500];
memset(dp,false,sizeof(dp));
dp[0][0] = true;
for (i = 1; i <= plen; ++i) {
dp[i][0] = dp[i - 1][0] && *(p + i -1) == '*';
for (j = 1; j <= slen; ++j) {
if (*(p + i -1) == '*')
dp[i][j] = dp[i][j - 1] || dp[i - 1][j];
else
dp[i][j] = dp[i - 1][j - 1] && (*(p + i -1) == *(s + j -1) || *(p + i -1) == '?');
}
}
return dp[plen][slen];
}
};
DP Solution:
f[i][j] indicates whether p[0..i] matches s[0..j]. So
if p[i] == '*', dp[i][j] = dp[i][j-1] || dp[i-1][j]
if p[i] != '*', dp[i][j] = dp[i-1][j-1] && single match
reduce two-dimension dp to 1 dimension
class Solution:
def isMatch(self, s, p):
slen, plen = len(s), len(p)
if (plen <= 0):
return slen == 0
if (slen <= 0):
return all(pi == '*' for pi in p)
f = [p[0] == '*' for i in range(slen)]
f[0] = (p[0] == '*' or p[0] == s[0] or p[0] == '?')
match_empty = [False for i in range(plen)] #以i结尾的p是否和s的空前缀匹配
match_empty[0] = p[0] == '*'
for i in range(1, plen):
match_empty[i] = (match_empty[i-1] and p[i] == '*')
#print(f)
for i in range(1, plen):
pre = list(f)
for j in range(0, slen):
if (p[i] == '*'):
#f[i][j] = f[i][j-1] || f[i-1][j]
tmp2 = f[j-1] if j >= 1 else match_empty[i-1]
f[j] = f[j] or tmp2
else:
#f[i][j] = f[i-1][j-1]
match = (p[i] == s[j]) or (p[i] == '?')
tmp = pre[j-1] if j >= 1 else match_empty[i-1]
f[j] = tmp and match
#print(f)
return f[-1]
s = Solution()
print(s.isMatch("aa","a"))
print(s.isMatch("aa","aa"))
print(s.isMatch("aaa","a"))
print(s.isMatch("aa","*"))
print(s.isMatch("aa","a*"))
print(s.isMatch("ab","?*"))
print(s.isMatch("aab","c*a*b"))
print(s.isMatch("adceb","*a*b"))
print(s.isMatch("a","a*"))

本文介绍了一种实现通配符匹配的算法,该算法支持 '?' 和 '*' 两种通配符,其中 '?' 可以匹配任意单个字符,而 '*' 可以匹配任意长度的字符序列。文中提供了贪婪算法及动态规划算法的实现,并通过多个实例验证了算法的有效性。
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