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Practical fast searching in strings
 Software Practice and Experience
, 1980
"... The problem of searching through text to find a specified substring is considered in a practical setting. It is discovered that a method developed by Boyer and Moore can outperform even specialpurpose search instructions that may be built into the, computer hardware. For very short substrings howev ..."
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Cited by 147 (0 self)
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The problem of searching through text to find a specified substring is considered in a practical setting. It is discovered that a method developed by Boyer and Moore can outperform even specialpurpose search instructions that may be built into the, computer hardware. For very short substrings
A Fast Quantum Mechanical Algorithm for Database Search
 ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING
, 1996
"... Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic)
will need to look at a minimum of names. Quantum mechanical systems can be in a supe ..."
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Cited by 1135 (10 self)
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Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic)
will need to look at a minimum of names. Quantum mechanical systems can be in a superposition of states and simultaneously examine multiple names. By properly adjusting the phases of various operations, successful computations reinforce each other while others interfere randomly. As a result, the desired phone number can be obtained in only steps. The algorithm is within a small constant factor of the fastest possible quantum mechanical algorithm.
The FF planning system: Fast plan generation through heuristic search
 Journal of Artificial Intelligence Research
, 2001
"... We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be ind ..."
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Cited by 830 (55 self)
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We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts
Predictive Indexing for Fast Search
"... We tackle the computational problem of queryconditioned search. Given a machinelearned scoring rule and a query distribution, we build a predictive index by precomputing lists of potential results sorted based on an expected score of the result over future queries. The predictive index datastructu ..."
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Cited by 6 (0 self)
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We tackle the computational problem of queryconditioned search. Given a machinelearned scoring rule and a query distribution, we build a predictive index by precomputing lists of potential results sorted based on an expected score of the result over future queries. The predictive index
Fast searching in packed strings,
 J. Discrete Algorithms
, 2011
"... Abstract. Given strings P and Q the (exact) string matching problem is to find all positions of substrings in Q matching P . The classical KnuthMorrisPratt algorithm [SIAM J. Comput., 1977] solves the string matching problem in linear time which is optimal if we can only read one character at th ..."
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Cited by 7 (2 self)
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Abstract. Given strings P and Q the (exact) string matching problem is to find all positions of substrings in Q matching P . The classical KnuthMorrisPratt algorithm [SIAM J. Comput., 1977] solves the string matching problem in linear time which is optimal if we can only read one character at the time. However, most strings are stored in a computer in a packed representation with several characters in a single word, giving us the opportunity to read multiple characters simultaneously. In this paper we study the worstcase complexity of string matching on strings given in packed representation. Let m ≤ n be the lengths P and Q, respectively, and let σ denote the size of the alphabet. On a standard unitcost wordRAM with logarithmic word size we present an algorithm using time Here occ is the number of occurrences of P in Q. For m = o(n) this improves the O(n) bound of the KnuthMorrisPratt algorithm. Furthermore, if m = O(n/ log σ n) our algorithm is optimal since any algorithm must spend at least Ω( (n+m) log σ log n + occ) = Ω( n log σ n + occ) time to read the input and report all occurrences. The result is obtained by a novel automaton construction based on the KnuthMorrisPratt algorithm combined with a new compact representation of subautomata allowing an optimal tabulationbased simulation.
Fastmap: A fast algorithm for indexing, datamining and visualization of traditional and multimedia datasets
, 1995
"... A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in kd space, using k featureextraction functions, provided by a domain expert [Jag91]. Thus, we can subsequently use highly finetuned spatial access methods (SAMs), to answer several ..."
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Cited by 502 (22 self)
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A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in kd space, using k featureextraction functions, provided by a domain expert [Jag91]. Thus, we can subsequently use highly finetuned spatial access methods (SAMs), to answer several
Fast Planning Through Planning Graph Analysis
 ARTIFICIAL INTELLIGENCE
, 1995
"... We introduce a new approach to planning in STRIPSlike domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partialorder plan, or states that no valid pla ..."
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Cited by 1171 (3 self)
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by Graphplan are quite sensible. Since searches made by this approach are fundamentally different from the searches of other common planning methods, they provide a new perspective on the planning problem.
Fast probabilistic algorithms for verification of polynomial identities
 J. ACM
, 1980
"... ABSTRACT The starthng success of the RabmStrassenSolovay pnmahty algorithm, together with the intriguing foundattonal posstbthty that axtoms of randomness may constttute a useful fundamental source of mathemaucal truth independent of the standard axmmaUc structure of mathemaUcs, suggests a wgorous ..."
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Cited by 520 (1 self)
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wgorous search for probabdisuc algonthms In dlustratmn of this observaUon, vanous fast probabdlsttc algonthms, with probability of correctness guaranteed a prion, are presented for testing polynomial ldentmes and propemes of systems of polynomials. Ancdlary fast algorithms for calculating resultants
Fast subsequence matching in timeseries databases
 PROCEEDINGS OF THE 1994 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
, 1994
"... We present an efficient indexing method to locate 1dimensional subsequences within a collection of sequences, such that the subsequences match a given (query) pattern within a specified tolerance. The idea is to map each data sequence into a small set of multidimensional rectangles in feature space ..."
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Cited by 533 (24 self)
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compared the method to sequential scanning, which is the only obvious competitor. The results were excellent: our method accelerated the search time from 3 times up to 100 times.
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