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.
简介:【摘要】近年来关于限价指令簿和指令驱动市场的研究成为理论界与实务界共同关注的一个问题。由于在指令驱动市场中投资者的行动空间、状态空间以及决策时点的维度都大大增加,研究难度也大大提高,该领域的研究在国外尚处于起步阶段,在国内则几近空白。早期的静态均衡模型研究的重点主要在于描绘加总的LOB形状,以及不同市场机制的比较。近年来很多学者将外生决定的指令选择这一假设修改为内生决定的指令选择,从而将LOB的理论研究从静态均衡模型推向了动态均衡模型。LB的实证研究则主要包括指令簿和指令流的特征分析、指令的激进性、指令的不衡、指令簿的信息内涵以及指令簿透明度与市场质量等方面。但相对于指令驱动市场目前在全球证券交易中所占的绝对重要地位而言,关于指令簿和指令驱动市场的研究仍处于起步阶段,有待于进一步深入拓展。