Rabin karp string matching algorithm

Rabin-Karp String Matching
Algorithm
-Gajanand Sharma
U V C E B A N G A L O R E
B A N G

Let a text string T of length n and a pattern string P of length m are given
such that m<=n, then the string matching problem is to find all occurrences
of P in T.
Example- T = “KARNATAKA” and P=“NAT”
Applications:
• Searching keywords in a file
• Searching engines
• Database searching
Problem Statement…

T : Given text or String e.g. – “JAIPURISCALLEDPARISOFINDIA”
|T| : 26, length of T
Substring: Ti,j=TiT i+1…Tj e.g. – “PARIS”
Subsequence of T: deleting zero or more characters from T
e.g. –“RISALL” and “JISINA”
Prefix of T: T1,k e.g. –“JAIPUR” is a prefix of T.
Suffix of T: Th,|T| e.g. –“INDIA” is a suffix of T.
Notations…

The Rabin-Karp string matching algorithm calculates a hash value for the
pattern, as well as for each M-character subsequence of given text to be
compared.
If the hash values for a particular subsequence are unequal, the algorithm
will calculate the hash value for next M-character sequence.
If the hash values are equal, the algorithm will do a Brute Force comparison
between the pattern and the M-character sequence.
Therefore there is only one comparison per text subsequence, and Brute
Force is only needed when hash values match.
Rabin-Karp Algorithm…

String:- LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLM
Pattern:-LLLLLM
Let Hash Value of “LLLLLL”= 0;
And Hash Value of “LLLLLM”= 1;
Step-1: LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLM
LLLLLM ------------ 0 != 1 (One Comparison)
Step-2: LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLM
LLLLLM ------------ 0 != 1(One Comparison)
:::: :::: :::: :::: :::: ::::
:::: :::: :::: :::: :::: ::::
Step-N: LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLM
LLLLLM --------- 1 = 1
Hash Value is matching so compare elements one by one.- (6+1 Comparisons)
Rabin-Karp Example…

Length of pattern = M;
Hash(p) = hash value of pattern;
Hash(t) = hash value of first M letters in body of text;
do
if (hash(p) == hash(t))
brute force comparison of pattern and selected section of
text
hash(t) = hash value of next section of text, one character
over
while (end of text or brute force comparison == true)
Pseudo Code…

Let’s associate one integer with every letter of the alphabet.
Hence we can say ‘A’ corresponds to 1, ‘B’ corresponds to 2 , ‘C’
corresponds to 3……
Similarly all other letters are corresponding to their index values.
The Hash Value of the String “CAT” will be-
3*100 + 1*10 + 20 = 330
Calculating Hash Value…
Index Position

If the hash value matches for two strings then it is called a ‘hit’.
It may be possible that two or more different strings produce the same hash
value.
String 1: “CBJ” hash code=3*100 + 2*10 + 10 = 330
String 2: “CAT” hash code=3*100 + 1*10 + 20 = 330
Hence it is necessary to check whether it is a hit or not?
Any hit will have to be tested to verify that it is not spurious and that p[1..m] =
T[s+1..s+m]
What if two values collide…

Let’s take an m-character sequence as an m-digit number in base b.
The text subsequence t[ i .. i + m-1] is mapped to the number as
follows-
x(i) = t[i].𝑏 𝑚−1
+ t[i+1].𝑏 𝑚−2
+ t[i+2].𝑏 𝑚−3
+………..t[i+m-1]
If m is very large then the hash value will be very large in size, so we
can hash the value by taking mod a prime number, say q.
h(i)=((t[i] 𝑏 𝑚−1
mod q) +(t[i+1] 𝑏 𝑚−2
mod q) + ...+(t[i+M-1] mod q))mod q
Mathematical Function…

• If a large prime number is used to calculate hash function then there a
very low possibility of being hashed values equal for two different
patterns.
• In this case searching takes O(N) time, where N is number of
characters in the text body.
• In worst case the time complexity may be O(MN), where M is no. of
characters in the pattern. This case may occur when the prime no.
chosen is very small.
Complexity…

Rabin karp string matching algorithm

Rabin karp string matching algorithm

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