简介:Whenqueryingonalarge-scaleknowledgebase,amajortechniqueofim-provingperformanceistopreloadknowledgetominimizethenumberofroundtripstotheknowledgebase.Inthispaper,anontology-basedsemanticcacheisproposedforanagentandontology-orientedknowledgebase(AOKB).InAOKB,anontologyisthecollectionofre-lationshipsbetweenagroupofknowledgeunits(agentsand/orothersub-ontologies).WhenloadingsomeagentA,itsrelationshipswithotherknowledgeunitsareexamined,andthosewhohaveatightsemantictiewithAwillbepreloadedatthesametime,includingagentsandsub-ontologiesinthesameontologywhereAis.Thepreloadedagentsandontologiesaresavedatasemanticcachelocatedinthememory.Testresultsshowthatupto50%reductioninrunningtimeisachieved.
简介:TheproblemofcontinuouslymonitoringmultipleK-nearestneighbor(K-NN)querieswithdynamicobjectandquerydatasetisvaluableformanylocation-basedapplications.Apracticalmethodistopartitionthedataspaceintogridcells,withbothobjectandquerytablebeingindexedbythisgridstructure,whilesolvingtheproblembyperiodicallyjoiningcellsofobjectswithquerieshavingtheirinfluenceregionsintersectingthecells.Intheworstcase,allcellsofobjectswillbeaccessedonce.ObjectandquerycachestrategiesareproposedtofurtherreducetheI/Ocost.Withobjectcachestrategy,queriesremainingstaticincurrentprocessingcycleseldomneedI/Ocost,theycanbereturnedquickly.ThemainI/Ocostcomesfrommovingqueries,thequerycachestrategyisusedtorestricttheirsearch-regions,whichusescurrentresultsofqueriesinthemainmemorybuffer.Thequeriescansharenotonlytheaccessingofobjectpages,butalsotheirinfluenceregions.TheoreticalanalysisoftheexpectedI/Ocostispresented,withtheI/Ocostbeingabout40%thatoftheSEA-CNNmethodintheexperimentresults.