Wrote for a long time forgot to save, embarrassed, first put here
Catalogue
1. tf-IDF2. Cosine algorithm based on space vector 3. Longest common sub-sequence 4. Minimum editing distance algorithm 5. Similar_text
1. TF-IDF
Relevant Link:
http://qianxunniao.iteye.com/blog/1831780
2. Cosine algorithm based on space vector
After the word frequency as a vector component, each file is converted into a vector, by calculating the cosine between the vectors, essentially calculating the similarity of the frequency of different texts.
3. Longest common sub-sequence
The biggest drawback of this algorithm is that CPU consumption is computationally large
1 . Two strings are composed of rows and columns in a matrix 2 . Calculates whether the row and column characters are the same for each node, or 1 if the same. 3
To further enhance the algorithm, we can add the value of the same node to the upper left corner (D[i-1,j-1]) to get the maximum length of the common substring. As a result, you can intercept the maximum substring simply by the line number and the maximum value.
Relevant Link:
HTTPS://segmentfault.com/q/1010000000738974http://www.speedphp.com/ thread-4840-1-1.htmlhttp://www.cnblogs.com/liangxiaxu/archive/2012/05/05/2484972.html
4. Minimum editing distance algorithm
Set A, B is two strings, the narrow editing distance is defined as the minimum required to convert a to B (delete a character in a), insert (insert a character in a) and replace (a character in a to replace the other character) the number of times, with an Ed (A, B) to represent. Intuitively, the more steps required to convert two strings to each other, the greater the difference
1. Process the two-part text and replace all non-text characters with the fragment marker "#"2. Longer text as the base text, traversing the short text after the fragment, found that the long texts contain the short sentence after the length of the article removed, did not find the matching words cumulative length 3. Compare the length of the remaining text with the length of the two paragraphs and its ratio to the mismatch ratio
The Levenshtein () function in PHP has already implemented this function
Relevant Link:
http://php.net/manual/zh/function.levenshtein.php
5. Similar_text
Relevant Link:
http://php.net/manual/zh/function.metaphone.phphttp://php.net/manual/zh/ function.soundex.phphttp://
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PHP Similarity algorithm