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Candidate Set Strategies for Ant Colony
"... Abstract. Ant Colony Optimisation based solvers systematically scan the set of possible solution elements before choosing a particular one. Hence, the computational time required for each step of the algorithm can be large. One way to overcome this is to limit the number of element choices to a sens ..."
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sensible subset, or candidate set. This paper describes some novel generic candidate set strategies and tests these on the travelling salesman and car sequencing problems. The results show that the use of candidate sets helps to find competitive solutions to the test problems in a relatively short amount
Mining Frequent Patterns without Candidate Generation: A FrequentPattern Tree Approach
 DATA MINING AND KNOWLEDGE DISCOVERY
, 2004
"... Mining frequent patterns in transaction databases, timeseries databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriorilike candidate set generationandtest approach. However, candidate set generation is still co ..."
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Cited by 1757 (64 self)
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Mining frequent patterns in transaction databases, timeseries databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriorilike candidate set generationandtest approach. However, candidate set generation is still
Candidate Sets for Complex Interval Arithmetic
, 1999
"... Uncertainty of measuring complexvalued physical quantities can be described by complex sets. These sets can have complicated shapes, so we would like to find a good approximating family of sets. Which approximating family is the best? We reduce the corresponding optimization problem to a geometric ..."
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is consistent with the fact that such sets have indeed been successful in computations. It stimulates to study further candidates. Construction of Optimal Families A practical problem leading to complex sets. Many physical quantities are complexvalued: wave function in quantum mechanics, complex amplitude
Candidate Set Strategies for Ant Colony Optimisation ∗
, 2008
"... Ant Colony Optimisation is a maturing class of metaheuristic search algorithms for discrete optimisation problems that are being increasingly applied to real world problems in areas such as communications and transportation. As these techniques systematically scan the set of possible solution eleme ..."
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elements before choosing a particular one, the computational time required for each step of the algorithm can be large. One way to overcome this is to limit the number of element choices to a sensible subset, or candidate set. This paper describes some novel generic candidate set strategies and tests
Computational Optimality Theory with finite candidate sets∗
"... • CCamelOT is an opensource webbased program that takes an input and a constraint ranking, and finds the output using OTCC. • OTCC (“OT with Candidate Chains”,?) is a theory of phonology with finite candidate sets, so CCamelOT can produce complete candidate sets and find the outputs in them. • ..."
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• CCamelOT is an opensource webbased program that takes an input and a constraint ranking, and finds the output using OTCC. • OTCC (“OT with Candidate Chains”,?) is a theory of phonology with finite candidate sets, so CCamelOT can produce complete candidate sets and find the outputs in them
Computational Optimality Theory with finite candidate sets∗
, 2006
"... • CCamelOT is an opensource webbased program that takes an input and a constraint ranking, and finds the output using OTCC. • OTCC (“OT with Candidate Chains”, McCarthy 2006) is a theory of phonology with finite candidate sets, so CCamelOT can produce complete candidate sets and find the output ..."
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• CCamelOT is an opensource webbased program that takes an input and a constraint ranking, and finds the output using OTCC. • OTCC (“OT with Candidate Chains”, McCarthy 2006) is a theory of phonology with finite candidate sets, so CCamelOT can produce complete candidate sets and find
An Empirical Model of Candidate Set Generation in Information Retrieval
"... Abstract: String Transformation is still an important research issue in the field of natural language processingand search engine optimization, Even though various traditional approaches available for string transformation they are not optimal because of Accuracy and efficiency are the basic paramet ..."
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parameters to optimize. While generation of the output Strings, Initially we consider the set of similar keywords. In this paper we are proposing an efficient approach of String transformation with Candidate generation and Selection and Query Reformulation, for the generation of the candidate sets we
Coarsetofine nbest parsing and MaxEnt discriminative reranking
 In ACL
, 2005
"... Discriminative reranking is one method for constructing highperformance statistical parsers (Collins, 2000). A discriminative reranker requires a source of candidate parses for each sentence. This paper describes a simple yet novel method for constructing sets of 50best parses based on a co ..."
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Cited by 522 (15 self)
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Discriminative reranking is one method for constructing highperformance statistical parsers (Collins, 2000). A discriminative reranker requires a source of candidate parses for each sentence. This paper describes a simple yet novel method for constructing sets of 50best parses based on a
StrategyProofness and Arrow’s Conditions: Existence and Correspondence Theorems for Voting Procedures and Social Welfare Functions
 J. Econ. Theory
, 1975
"... Consider a committee which must select one alternative from a set of three or more alternatives. Committee members each cast a ballot which the voting procedure counts. The voting procedure is strategyproof if it always induces every committee member to cast a ballot revealing his preference. I pro ..."
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Cited by 552 (0 self)
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Consider a committee which must select one alternative from a set of three or more alternatives. Committee members each cast a ballot which the voting procedure counts. The voting procedure is strategyproof if it always induces every committee member to cast a ballot revealing his preference. I
Diagnosing multiple faults.
 Artificial Intelligence,
, 1987
"... Abstract Diagnostic tasks require determining the differences between a model of an artifact and the artifact itself. The differences between the manifested behavior of the artifact and the predicted behavior of the model guide the search for the differences between the artifact and its model. The ..."
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Cited by 807 (62 self)
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in the domain of troubleshooting digital circuits. This research makes several novel contributions: First, the system diagnoses failures due to multiple faults. Second, failure candidates are represented and manipulated in terms of minimal sets of violated assumptions, resulting in an efficient diagnostic
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