knuth-morris-pratt

问题 I am trying to find the next table of the following DFA graph using knuth-morris-pratt (KMP).The DFA for searching for the string "cbcbca". I have seen some tutorials but didn't find a good one. Any help will be appreciatable about how to draw the table with step. Thanks. 来源： https://stackoverflow.com/questions/62496036/how-can-i-write-next-table-or-next-array-using-knuth-morris-pratt-algorithm

问题 I am reading about the KMP substring search algorithm and the examples I find online use an one-dimensional table to build the prefix information table. I also read the Sedgewick explanation and he used a 2-D array to build the table and explicitly states that the space complexity of KMP is O(RM) where R is the alphabet size and M the pattern size while everywhere else it is stated that the space complexity is just O(M + N) i.e. the text to process and the pattern size itself. So I am

来源： https://stackoverflow.com/questions/60853582/why-how-does-the-longest-proper-prefix-suffix-algorithm-work

问题 I read the source code of java.lang.String and I was surprised to find that String.indexof() does not use the Knuth–Morris–Pratt algorithm? As we know, KMP is more effective. So why isn't it used in String.indexOf() ? Someone around me told me that for short string KMP is good enough, but if you need performance and you intend to use with large strings then is not a good choice. However he didn't tell me the details. So, here are my questions: why don't we use KMP in String.indexOf() ? why is

问题 I read the source code of java.lang.String and I was surprised to find that String.indexof() does not use the Knuth–Morris–Pratt algorithm? As we know, KMP is more effective. So why isn't it used in String.indexOf() ? Someone around me told me that for short string KMP is good enough, but if you need performance and you intend to use with large strings then is not a good choice. However he didn't tell me the details. So, here are my questions: why don't we use KMP in String.indexOf() ? why is

问题 I tried to solve the problem of two dimensional search using a combination of Aho-Corasick and a single dimensional KMP, however, I still need something faster. To elaborate, I have a matrix A of characters of size n1*n2 and I wish to find all occurrences of a smaller matrix B of size m1*m2 and I want that to be in O(n1*n2+m1*m2) if possible. For example: A = a b c b c b b c a c a c d a b a b a q a s d q a and B = b c b c a c a b a the algorithm should return the indexes of say, the upper

问题 I'm reading the KMP algorithm on wikipedia. There is one line of code in the "Description of pseudocode for the table-building algorithm" section that confuses me: let cnd ← T[cnd] It has a comment: (second case: it doesn't, but we can fall back) , I know we can fall back, but why T[cnd], is there a reason? Because it really confuses me. Here is the complete pseudocode fot the table-building algorithm: algorithm kmp_table: input: an array of characters, W (the word to be analyzed) an array of

问题 I've tried my best reading most of the literature on this, and still haven't understood anything about how the failure function used in KMP algorithm is constructed. I've been referring mostly to http://community.topcoder.com/tc?module=Static&d1=tutorials&d2=stringSearching tutorial which most of the people consider excellent. However, I still have not understood it. I'd be thankful if you could take the pain of giving me a simpler and easy to understand explanation on it. 回答1: The failure

问题 I have a trouble with understanding this implementation of the Knuth-Morris-Pratt algorithm in Haskell. http://twanvl.nl/blog/haskell/Knuth-Morris-Pratt-in-Haskell In particular I don't understand the construction of the automaton. I know that it uses the "Tying the Knot" method to construct it, but it isn't clear to me and I also don't know why it should have the right complexity. Another thing I would like to know is whether you think that this implementation could be easily generalized to

问题 What are the available string matching algorithms besides Knuth-Morris-Pratt, Rabin-Karp and likes of it? 回答1: A well cited compendium of these algorithms can be found in: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.133.4896&rep=rep1&type=pdf Included are the following algorithms: Karp-Rabin Shift Or Morris-Pratt Knuth-Morris-Pratt Simon Colussi Galil-Giancarlo Apostolico-Crochemore Not So Naive Forward Dawg Matching Boyer-Moore Turbo-BM Apostolico-Giancarlo Reverse Colussi