Publication | Closed Access
Optimal aggregation algorithms for middleware
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Citations
21
References
2001
Year
Unknown Venue
Cluster ComputingRanking AlgorithmEngineeringOptimal Aggregation AlgorithmsData AggregationLearning To RankAggregate FunctionInformation RetrievalData ScienceData MiningParallel ComputingCombinatorial OptimizationMonotone Aggregation FunctionStatisticsMiddlewareSorting AlgorithmKnowledge DiscoveryComputer ScienceColor GradeDistributed MiddlewareMiddleware SystemParallel ProgrammingM AttributesData Modeling
Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade under that attribute, sorted by grade (highest grade first). There is some monotone aggregation function, or combining rule, such as min or average, that combines the individual grades to obtain an overall grade.
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