A. V. Aho and M. J. Corasick. Efficient string matching: an aid to bibliographic search. Commun. ACM, 18(6):333--340, 1975. # Engines (r) # hash Total on-chip Theoretical Observed functions(h) memory bits  Home/Search   Document Not in Database   Summary   Related Articles   Check

....the KMP automaton [19] This view enables us to simplify the algorithm and then extend it to the multiple pattern matching problem. In this paper, we give an algorithm for finding multiple patterns in an LZW com pressed text. It simulates the move of the Aho Corasick multipattern matching machine [2]. The algorithm runs in O(n m 2 r) time using O(n m 2) space, where n is the length of the compressed text, m is the total length of the patterns, and r is the number of occurrences of the patterns. The O(r) time is devoted only to reportifig the positions of the pattern occurrences. It is ....

....trie. Method. D : E; for i : I to n I do begin if uid 1 IDI then let a be the first character of let a be the first character of ui; D : D U ui a) end. FIG. 2. Reconstruction of dictionary trie. 3. 2 Aho Corasick pattern matching machine The Aho Corasick pattern matching machine [2] (AC machine for short) is a finite state machine which simultaneously recognizes all occurrences of multiple patterns in a single pass through a text. The AC machine for a finite set II C E of patterns is specified by the three functions: goto function g: Q x E Q u fail , failure ....

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A. V. Aho and M.J. Corasick. Efficient string matching: An aid to bibliographic search. Comm. ACM, 18(6):333-340, 1975.

....closure of the hypernym relation and use (5) to calculate the conceptual similarities. Phrase Detection Given a set of documents (106 queries and 14K judged documents of OSHUMED) we need to detect any occurrences in a set of phrases (1. 3M phrases in UMLS) We adopt the Aho Corasick algorithm [15] for the set matching problem to detect phrases: First, Aho Corasick algorithm detects all occurrences of any phrase in a document. But we only keep the longest, most specific phrase. For example, although both edema and cerebral edema are detected in the sample query, we keep only the latter ....

A.V. Aho and M.J. Corasick. Efficient String Matching: an Aid to Bibliographic Search. In CACM, 18(6), 330340, 1975

....hypernym of hyperthermia. However UMLS Metathesaurus encodes only the direct hypernym relations but not the transitive closure. We derive the transitive closure of the hypernym relation and use (5) to calculate the conceptual similarities. Phrase Detection We adopt the Aho Corasick algorithm [14] for the set matching problem to detect each occurrences in a set of phrases (1.3M phrases in UMLS) in a set of documents (106 queries and 14K judged documents of OSHUMED) First, Aho Corasick algorithm detects all occurrences of any phrase in a document. But we only keep the longest, most ....

A.V. Aho and M.J. Corasick. Efficient String Matching: an Aid to Bibliographic Search. In CACM, 18(6), 330-340, 1975

.... characters from separate state to m to the terminal state is called a single string for m, denoted as STR[m] The separate states in Figure 1 are 3, 12, 14, 24 and 33, and single strings that correspond to each separate state are as follows: STR[3] lusion# , STR[12] the empty string) STR[14] = iration# , STR[24] llation# , STR[33] ument# . DAWG (directed acyclic word graph) A DAWG 21,22 is the typical structure reducing the number of states in the trie. DAWGs do not require the endmarker # for each key. Figure 2 shows the DAWG for K1. The total number of states in the ....

....so from expressions (1) and (2) above LH BASE[1] i = 11 Observe that LH CHECK[11] 1. Step 2. Since the value found for LH BASE in step 1 is positive, proceed. Use the value 11 from step 1 as the new index into LH BASE, and value 13 for character l , so LH BASE[11] l = 14 and LH CHECK[14] = 11 LH BASE[14] 2( 0) Step 3. The value in LH BASE[14] is 2. If this searched character is the endmarker #, then retrieval finishes successfully, but in this case the character l is not the endmarker #. So proceed. A negative value indicates that the rest of the key is stored in the RH ....

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A. V. Aho and M. J. Corasick, `Efficient string matching: an aid to bibliographic search', Commun. ACM., 18, (6), 333--340 (1975).

....a record of the cache misses. We propose to evaluate hardware assists that automatically detect changes in the memory grain size and context sets. This hardware would be synthesized to implement a cache tag recognizer using a modified version of the Aho Corasic algorithm for string matching [2]. If the recognizer detected a desirable configuration change, the hardware modifications could be precomputed or even synthesized on the fly, and programmed into the appropriate hardware. 3.2 Profiling and Programmer Annotation While a full complement of programmer annotation, profile directed ....

Aho, A., and Corasick, M. Efficient String Matching: An Aid to Bibliographic Search. Commun. ACM 18, 6 (June 1975), 333--340.

....Our problem is slightly different, we are searching for one of a set of strings from the input stream. Instead of simply iterating a standard one string matching algorithm, the set of strings that we are looking for can be folded into a single statemachine. This method, the Aho Corasick algorithm [2], is what is used in the fgrep utility as well as the latest versions of the Snort [20] network intrusion detection system. The Aho Corasick algorithm works by building up a state machine that is fed the string to be searched. The state machine is generated by building up a tree of all the ....

A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

....where n is the length of the compressed text. 5 4 3 2 1 10 9 8 7 6 12 11 a a a a a b b b b c c b a b ab ab ba b c aba bc abab 1, 2, 4, 4, 5, 2, 3, 6, 9, 11 original text: compressed text: Figure 1: Dictionary trie. 2. 2 AC machine The Aho Corasick pattern matching machine[1] (AC machine for short) is a finite state machine which simultaneously locates all occurrences of multiple patterns in a single pass through a text. The construction of the AC machine takes only linear time proportional to the sum of the lengths of the patterns. Let 6 be an alphabet. Let 5 ....

....and space, and the construction of the GST for 5 takes O(m ) time and space, where m is the total length of patterns in 5. Now, we consider the realization of Next. The following lemma characterizes the state transition function ffi of the AC machine. This is a modified version of Lemma 3 in [1]. Lemma 1 Let q Q = Prefix(5) u , and let p = ffi(q; u) Then, the string p is the longest string in the set Suffix(qu) Q. Let 5 be a finite set of patterns, and let u . Define Occ(5;u) fq Prefix(5) qu Prefix(5)g: The set Occ(5;u) means the set of states in Q = ....

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A. V. Aho and M. Corasick. Efficient string matching: An aid to bibliographic search. Comm. ACM, 18(6):333--340, 1975.

....a multipattern exact search algorithm for all the pieces. Each time a piece is found, it uses dynamic programming over an area of length m 2k where the approximate occurrence can be found. The multipattern search can be carried out in O(n) worst case search time by using an Aho Corasick machine [1], or in O(n=m) best case time using Commentz Walter [15] or another Boyer Moore type algorithm adapted to multipattern search. The total cost of verifications keeps negligible if k=m 1= 3 log m) We call sublinear time those algorithms that do not inspect all the text characters. On the other ....

....approximate pattern matching. 7.1 Exact Multidimensional Pattern Matching In [12] they allow searching, in two dimensions, a pattern in a text in O(n =m) average time. They traverse only the text rows of the form i m searching for all the pattern rows at the same time (using Aho Corasick [1]) and verify all potential matches. Clearly, no match can be missed with the filter. In [12] the authors briefly mention that their technique can be extended to more dimensions by selecting one dimension and recursively using an algorithm for (d 1) dimensions on the m th rows of such text. ....

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A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. CACM, 18(6):333-- 340, June 1975.

....and verification time. 3.1 Faster Search Following [3, 4] we propose to search more features of the pattern to reduce the number of text rows to consider. This has obvious advantages since the search time per character is independent on the number of patterns if an Aho Corasick machine (AC) [1] is used. In [4] a 2 dimensional search algorithm (not allowing rotations) is proposed by searching all the pattern rows in the text, so that only the text rows multiples of m need to be considered because one of them must contain some pattern row in any occurrence. We take a similar approach. ....

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. CACM, 18(6):333--340, June 1975.

....[7] BYP, in short) improved BYP which considers the locations of the subsequences, and counting character occurrences [6] counting, in short) The first two were also tested in combination with the third technique. The search of the subsequences was implemented with the Aho Corasick algorithm [12]. The results are shown in Table 2. The length of subsequences was five. Thus, the length of 25 symbols includes five subsequences. Counting the character occurrences was rather inefficient. In fact its effect was negative to the whole process. On the other hand, adding sensitivity for ....

Aho A and Corasick M. Efficient string matching: an aid to bibliographic search. Comm ACM. 1975: 18: 33340. Address for correspondence Heikki Hyyr, Department of Computer and Information Sciences,

....except BNDM, which is presented in [5] In the second approach we compared the relative efficiency between keyword tree variants of the Brute Force and the KnuthMorris Pratt algorithms. The keyword tree version of the Knuth Morris Pratt algorithm is generally known as the Aho Corasick algorithm [6]. A difficulty in the third approach was that the keyword tree may become too large to fit into the main memory of the computer. We solved this problem by dividing the oligonucleotides of the genome into different groups according to their Karp Rabin fingerprints. This basically means calculating ....

Aho A and Corasick M. Efficient string matching: an aid to bibliographic search. Communications of the ACM. 1975: 18: 333-40.

....We now show how to answer Q1 and Q2 in O(1) time by preprocessing the primary terms s and p into a string matching automaton. 3.1.3 Preprocessing Primary Terms Central to our technique is a finite state automaton that is constructed from the primary strings. We use the Aho and Corasick (see [1] for details) algorithm to construct such an automaton. Following [1] we refer to the strings recognized by the automaton as the keywords of the automaton. The automaton consists of nodes called states and two types of links goto and failure. The goto links are labeled with symbols from the ....

....the primary terms s and p into a string matching automaton. 3.1.3 Preprocessing Primary Terms Central to our technique is a finite state automaton that is constructed from the primary strings. We use the Aho and Corasick (see [1] for details) algorithm to construct such an automaton. Following [1] we refer to the strings recognized by the automaton as the keywords of the automaton. The automaton consists of nodes called states and two types of links goto and failure. The goto links are labeled with symbols from the alphabet of the keywords. These links together with the states form a ....

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A.V. Aho and M.J. Corasick, Efficient String Matching: An Aid to Bibliographic Search, CACM, Vol. 18 No. 6, 1975, pp. 333-340.

....a regular expression; any sequence that contains a string from the regular expression s language as a substring is part of the family, or contains the feature. Searching for strings from a language defined by a regular expression can be done with a scanning algorithm that uses an automaton table [AC75]. If the string pattern is represented by a regular expression of length m, the table is built in O(m) time, and used to search a sequence of length n in O(n) time. If the pattern is instead represented by a finite collection of strings whose lengths sum to l, the automaton table takes O(l) time ....

....of length m, the table is built in O(m) time, and used to search a sequence of length n in O(n) time. If the pattern is instead represented by a finite collection of strings whose lengths sum to l, the automaton table takes O(l) time to build from the set. This algorithm of Aho and Corasick [AC75] is a generalization of the table based technique for string pattern matching given by Knuth, Morris, and Pratt [KMP77] A protein motif can also be characterized using a weight matrix, or profile. Each position in the matrix corresponds to the combination of a particular symbol and a position in ....

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. Communications of the Association for Computing Machinery 18 (1975), 333-340.

....playing at wheaton yes no Nell null Wheaton Table 2: Examples of annotated utterances. where is the when is the client playing in glen ellyn what romantic movies where are romantic movies playing The rightmost longest match can be determined efficiently by a variant of a well known algorithm [3] for matching finite sets of keywords. Rightmost longest pattern matching based on the dictionary in Figure 2 (we predict yes no by default, in case none of the keywords in the dictionary matched) achieves a baseline accuracy of 99.0 on the development corpus. This can be improved by training a ....

Alfred V. Aho and Margaret J. Corasick, "Efficient string matching: An aid to bibliographic search," Communications of the ACM, vol. 18, no. 6, pp. 333--340, 1975.

....; s 2 ) for each (s 1 ; s 2 ) 2 R; x 1: i = x 0 s 1 ; y 1: j = y 0 s 2 ) An interesting problem is how to compute this recurrence efficiently. A naive approach takes O(jRjmn) where jRj is the sum of all the lengths of the strings in R. A better solution is to build two Aho Corasick automata [AC75] with the left and right hand sides of the rules, respectively. The automata are run as we advance in both strings (left hand sides in x and right hand sides in y) For each pair of states (i 1 ; i 2 ) of the automata we precompute the set of replacements that can be tried (i.e. those ffi s ....

....and check the neighborhood of their matches (of length m 2k) They used an extension of Shift Or [BYG92] to search all the pieces simultaneously in O(mn=w) time. In the same 1992, Baeza Yates and Perleberg [BYP96] suggested better algorithms for the multipattern search: an Aho Corasick machine [AC75] to guarantee O(n) search time (excluding verifications) or Commentz Walter [CW79] Only in 1996 the improvement was really implemented [BYN99] by adapting the Boyer MooreSunday algorithm [Sun90] to multipattern search (using a trie of patterns and a pessimistic shift table) The resulting ....

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. Comm. of the ACM, 18(6):333--340, 1975.

.... appears or not) in time and space O(m 2 n) For LZ77 a randomized algorithm has been presented [FT98] to solve the same problem in time O(m n log 2 (u=n) An extension of the former work to multipattern searching on LZ78 LZW was later presented [KTS 98] Based on Aho Corasick [AC75] they achieve O(m 2 n R) time and O(m 2 n) space to find all the occurrences of the patterns, where this time m is the total length of all the patterns. Later work [NR99] presented a general scheme to search on Ziv Lempel compressed texts (simple and extended patterns) and specialized ....

....same. We describe now three possible techniques for the multipattern search. These are later compared in the experiments. 4. 1 An Aho Corasick Technique The multipattern search algorithm on LZ compressed text [KTS 98] is based on the simulation of the Aho Corasick pattern matching machine [AC75] A Mealy type sequential machine is built which processes the blocks one by one. It consists of two functions: Jump and Output defined on the domain Q Theta D, where Q is the set of states of the AC machine and D is the set of Ziv Lempel blocks. For every block b r , the machine makes just one ....

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. Comm. of the ACM, 18(6):333--340, June 1975. 9

....p w. This means that for constant ff and increasing m, pattern partitioning is asymptotically better. 6.2 Partitioning into Exact Searching In [6] we analyze this algorithm as follows. Except for verifications, the search time can be made O(n) in the worst case by using an Aho Corasick machine [1], and O(ffn) in the best case if we use a multipattern Boyer Moore algorithm. This is because we search pieces of length m= k 1) 1=ff. We are interested in analyzing the cost of verifications. Since we cut the pattern in k 1 pieces, they are of length bm= k 1)c or dm= k 1)e. The probability ....

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. CACM, 18(6):333--340, June 1975.

....search algorithm proposed by Baeza Yates and Navarro [BaezaYates and Navarro 1999] This algorithm is an extension of the Sunday algorithm, and works well when the number of patterns to search is not very large. In case of a large number of patterns to search, the best option would be Aho Corasick [Aho and Corasick 1975], which allows to search in O(n) time independently of the number of patterns. If we assume that the compressed codeword of a pattern of length m is c, then Boyer Moore type algorithms inspect about n=c bytes of the compressed text in the best case. This best case is very close to the average ....

Aho, A. and Corasick, M. 1975. Efficient string matching: an aid to bibliographic search. Communications of the ACM 18, 6, 333--340.

....2 R , r k matches t k R , where t i R is the remaining unexamined suffix of t R after r 1 ; r i Gamma1 have been matched. We have only one remaining problem to solve; namely, how do we do rigid component matching efficiently We propose the use of the Aho Corasick algorithm [2, 15] that computes occurrences in a given text of any string in a given finite set of pattern strings. The algorithm has two phases: In the first phase, the preprocessing phase, a deterministic finite state automaton is efficiently computed for the given set of pattern strings and, in the second ....

A.V. Aho and M.J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18:333--340, 1975.

.... else p = c; c = pop(manager) 3 File defined by scraps , 37 hCheck for end of scrap name and return i j c = pop(manager) if (c = p = c; c = pop(manager) else if (c = if (p name 3 p[ 1] = p[ 2] p[ 3] p[ 3] p = 2; p = 0 ; return prefixadd( macronames, name) else fprintf(stderr, s: found an internal problem (1) n , commandname) exit( 1) 3 Macro referenced in scrap . scraps.c j int writescraps(file, defs, globalindent, ....

....switch (c) case : p = c; break; case : hCleanup and install name i default: fprintf(stderr, s: unexpected c in macro name ( s, d) n , commandname, c, sourcename, startline) exit( 1) 3 Macro referenced in scrap . 49 hCleanup and install name i j if (p name p[ 1] = p ; if (p name 3 p[ 1] p[ 2] p[ 3] p[ 3] p = 2; if (p = name name[0] fprintf(stderr, s: empty scrap name ( s, d) n , commandname, sourcename, sourceline) exit( 1) p = 0 ; return prefixadd( macronames, name) 3 ....

[Article contains additional citation context not shown here]

Alfred V. Aho and Margaret J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, June 1975.

....a multipattern exact search algorithm for all the pieces. Each time a piece is found, it uses dynamic programming over an area of length m 2k where the approximate occurrence can be found. The multipattern search can be carried out in O(n) worst case search time by using an Aho Corasick machine [1], or in O(n=m) best case time using Commentz Walter [11] or another Boyer Moore type algorithm adapted to multipattern search. The total cost of verifications keeps below O(n) time provided k=m 1= 3 log oe m) Two dimensional string matching was first considered by Bird and Baker [10, 9] who ....

....(that is, s = 1) 6 Multidimensional Exact String Matching In [8] they allow to search, in two dimensions, a pattern in a text in O(n 2 =m) average time. They traverse only the text rows of the form i Theta m searching for all the pattern rows at the same time (using an Aho Corasick machine [1]) and verify all potential matches. It is easy to see that no match can be missed with the filter. 6 2 d text 2 d pattern 2 d pattern 3 d text 3 d pattern 3 d pattern Figure 2: Algorithm for exact searching. All the pattern rows are searched in n=m text rows at the same time. In [8] ....

[Article contains additional citation context not shown here]

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. CACM, 18(6):333-- 340, June 1975.

....of oe. The curve ff = 1 Gamma 1= p oe is included to show its closeness to the experimental data. Least squares give the approximation ff = 1 Gamma 1:09= p oe, with a relative error smaller than 1 . This shows that the upper bound analysis (Eq. 2) matches reality better, provided we replace e by 1:09 in the formulas. Therefore, we have shown that the matching probability has a sharp behavior: for low ff it is very low, not as low as 1=oe m like exact string matching, but still exponentially decreasing in m, with an exponent base larger than 1=oe. At some ff value (that we called ff ) it ....

....2 ) for each ffi (s 1 ; s 2 ) 2 R; x 1: i = x 0 s 1 ; y 1: j = y 0 s 2 ) An interesting problem is how to compute this recurrence efficiently. A naive approach takes O(jRjmn) where jRj is the sum of all the lengths of the strings in R. A better solution is to build two Aho Corasick automata [AC75] with the left and right hand sides of the rules, respectively. The automata are run as we advance in both strings (left hand sides in x and right hand sides in y) For each pair of states (i 1 ; i 2 ) of the automata we precompute the set of replacements that can be tried (i.e. those ffi s ....

[Article contains additional citation context not shown here]

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search.

....on the pattern y to speed up linear time algorithms for string matching both in practice and on the average. The suffix tree defined on a dynamic set of strings, instead of a single string, has been used by Amir et al. 6] to obtain a dynamic version of the static Aho Corasick dictionary automaton [2]. The Aho Corasick automaton finds the multiple occurrences of a given set fy 1 ; y k g of patterns simultaneously into a text x. In many applications, the text (e.g. the Oxford English Dictionary or a DNA sequence) is fixed and static, with the above string matching query being repeated ....

Aho, A. V., and Corasick, M. J., Efficient string matching: an aid to bibliographic search, Comm. ACM, 18 (1975), 333--340.

....# F ( of an FSA to speed up the matching process. The reader is warned against confusing the state transition function, #, with the letter substring #. Since both uses are established in the literature, we have refrained from changing one or other symbols. The first step is to build a trie [25, 26], augmented with transitions on the empty input #, to encode the set of correspondences. Figure 3 illustrates this in simplified form for the example correspondences in (3) The trie is then used to generate the state transition function # F ( FIGURE 3 ABOUT HERE The root of the trie ....

....Q d i =0 (# i 1) 2 # where d is the maximum depth of the trie and # i is the number of nodes in the trie at depth i . Theorem 3 If all the nodes in the trie have # transitions leading to S, then Q = # . Theorem 3 (which is actually implicit in the Aho Corasick construction [26] of a DFA from an NFA) does not, of course, state that Q = # in all practical cases of letter tophoneme translation. However, we now show that this equality holds quite generally. Let T 1 be the trie with (a) a root that has valid out transitions for each symbol in the input alphabet and ....

A.V. Aho and M.J. Corasick, "Efficient string matching: an aid to bibliographic search," Comm. ACM, vol. 18, pp. 333--340, 1975.

....with mismatch position i 1 and mismatch character strictly greater than T [i 1] This ensures that we exclude the exact occurrences of the patterns, as the reader may verify. The exact occurrences of the patterns of D in T can be determined separately in O(t) time by using classical algorithms [AC75]. The total search cost and space usage remains as in Theorem 8 (but notice that for other trade offs we get slightly different bounds than in the case where duplicates are reported, because we now have d = 3) 5 Concluding remarks Multi methods and dispatching. The introduction of multi methods ....

A. V. Aho and M. J. Corasick. Efficient string matching: an aid to bibliographic searching. Communications of the ACM, 18:333--340, 1975.

.... c, an m bits long mask t[c] representing match (0) or mismatch (1) against the pattern, and then computing a mask T [c] having at each block the (k 1) bits long segment of t[c] that is relevant to that block (see Figure 2) That is, t[c] c = pat[m] c = pat[m Gamma 1] c = pat[1]) where each condition stands for a bit and they are aligned to the right. So we precompute 0 1 1 0 x e t 0 0 1 1 t x e separator separator (0,1) 1,3) 0,2) 2,4) 1,2) final state 0 0 0 0 0 1 1 1 D (2,3) T[ t ] Fig. 2. Encoding of the example NFA. T [c] 0 s k 1 (t[c] 0) 0 s k 1 (t[c] 1) ....

....3 presents the complete algorithm. To avoid complications, we do not refine the preprocessing, which can be done more efficiently than what the code suggests. search (T ext; n; pat; m;k) f preprocessing for each c 2 Sigma f t[c] c = pat[m] c = pat[m Gamma 1] c = pat[1]) T [c] 0 sk 1 (t[c] 0) 0 sk 1 (t[c] 1) 0 sk 1(t[c] m Gamma k Gamma 1) S[c] c 2 pat[1: k 1] g Din = 0 1 k 1 ) m Gammak M1 = 0 k 1 1) m Gammak M2 = 0 k 1 1) m Gammak Gamma1 0 1 k 1 M3 = 0 (m Gammak Gamma1) k 2) 0 1 k 1 G = 1 k searching D = Din i ....

[Article contains additional citation context not shown here]

A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. CACM, 18(6):333--340, June 1975.

....certain patterns are supposed to be extracted. With our scheme the newsfeed can come in compressed, resulting in faster filtering. Although we discussed searching single patterns here, our scheme will work for searching multiple patterns with either the Aho Corasick algorithm used in fgrep [AC75] or with agrep s algorithm [WM92] If the setting is such that compression is already used, then, as we said in section 2.2, the original compression can come on top of our compression and the search can be performed after the original compression is removed. The same approach may also be used ....

Aho, A. V., and M. J. Corasick, "Efficient string matching: an aid to bibliographic search", Communications of the ACM, 18 (June 1975), pp. 333-340.

....and the text are both simple strings. The two famous algorithms for this string matching problem are the Boyer Moore algorithm [BM77] and the Knuth Morris Pratt algorithm [KMP77] The basic problem has been extended to include more complicated patterns, including a set of strings (Aho and Corasick [AC75] and Commentz Walter [CW79] strings with don t care symbols (Fischer and Paterson [FP74] and strings with don t care and complement symbols (Pinter [Pin85] Abrahamson [Abr87] studied the complexity of several matching problems and presented algorithms for strings with classes, which ....

Aho, A. V., and M. J. Corasick, "Efficient string matching: an aid to bibliographic search", Comm. of the ACM, 18 (June 1975), pp. 333-340.

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A. V. Aho and M. J. Corasick. Efficient string matching: an aid to bibliographic search. Commun. ACM, 18(6):333--340, 1975. # Engines (r) # hash Total on-chip Theoretical Observed functions(h) memory bits

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A. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, June 1975.

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A. Aho and M. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--343, June 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

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Alfred V. Aho and Margaret J. Corasick. Efficient string matching: an aid to bibliographic search. Communications of the ACM, 18(6):333--340, June 1975.

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Alfred V. Aho and Margaret J. Corasick. Efficient string matching: an aid to bibliographic search. Communications of the ACM, 18(6):333--340, June 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: an aid to bibliographic search. Communications of the ACM, 18(6):333--340, June 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333--340, 1975.

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A. V. Aho and M. J. Corasick. Efficient string matching: An aid to bibliographic search. Commun. ACM, 18(6):333--340, 1975.

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A. Aho and M. Corasick, Efficient string matching: an aid to bibliographic search. Comm. ACM, 18, pp. 333--340, 1975

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A. Aho and M. Corasick, Efficient string matching: An aid to bibliographic search, Comm. ACM 18 (1975), 333--340.

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A. V. Aho, M. Corasick, Efficient string matching: an aid to bibliographic search, Comm. ACM 18 (1975) 333--340.

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A. Aho and M. Corasick. Efficient string matching: an aid to bibliographic search. CACM, 18(6):333--340, June 1975.

No context found.

A. V. Aho and M. J. Corasick, `Efficient string matching: An aid to bibliographic search', Commun. ACM, 18(6), 333--340 (1975).

No context found.

A. V. Aho and M. J. Corasick, `Efficient string matching: an aid to bibliographic research', Comm. ACM 18(6), 333--340 (1975).

No context found.

AHO, A. V. AND CORASICK, M. J. Efficient string matching: An aid to bibliographic search. Comm. of ACM 18,6, June 1975.

No context found.

A.V. Aho and M.J. Corasick. Efficient string matching: An aid to bibliographic search. CACM, 18(6), 333-340.

No context found.

A.Aho and M.Corasick, "Efficient String Matching: An Aid to Bibliographic Search," Communications of ACM, Vol 18, No.6, June 1975, pp.333-340.

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