简介:Astheevolutionofmobiletechnology,mobiledeviceshavebecomeanessentialtoolinpeople’sdailylife.Moreover,withtherapidgrowthofInternetandmobilenetworks,peoplecaneasilyaccessvariousservicesprovidedbymobileplatforms.Manyservicescanbeexecutedonthemobiledeviceswithvariousmobileapplicationslaunchedtomobileplatforms.Peoplecanchoosewhattheyliketoinstallintheirmobiledevicesandhencemaketheirlifemoreconvenient,entertaining,andproductive.However,therearetoomanymobileapplicationsforuserstochoose.Thegoalofthisresearchistoproposeamethodologywhichcanrecommendtop-Nlistsformobileapplications.Acommentcorrelationmatrixisproposed.Furthermore,arecommendationalgorithmformobileapplicationsbasedonusercommentsandkeyattributesisbuilt.Withtheproposedmethod,itoutperformsGoogleplayandisclosertouserrealfeelings.
简介:SocialtaggingisoneofthemostimportantcharacteristicsofWeb2.0services,andsocialtaggingsystems(STS)arebecomingmoreandmorepopularforuserstoannotate,organizeandshareitemsontheWeb.Moreover,onlinesocialnetworkhasbeenincorporatedintosocialtaggingsystems.AsmoreandmoreuserstendtointeractwithrealfriendsontheWeb,personalizeduserrecommendationserviceprovidedinsocialtaggingsystemsisveryappealing.Inthispaper,weproposeapersonalizeduserrecommendationmethod,andourmethodhandlesnotonlytheusers'interestnetworks,butalsothesocialnetworkinformation.Weempiricallyshowthatourmethodoutperformsastate-of-the-artmethodonrealdatasetfromLast.fmdatasetandDouban.
简介:Thewidespreadoflocation-basedsocialnetworksbringsaboutahugevolumeofusercheck-indata,whichfacilitatestherecommendationofpointsofinterest(POIs).Recentadvancesondistributedrepresentationshedlightonlearninglowdimensionaldensevectorstoalleviatethedatasparsityproblem.CurrentstudiesonrepresentationlearningforPOIrecommendationembedbothusersandPOIsinacommonlatentspace,andusers'preferenceisinferredbasedonthedistance/similaritybetweenauserandaPOI.SuchanapproachisnotinaccordancewiththesemanticsofusersandPOIsastheyareinherentlydifferentobjects.Inthispaper,wepresentanoveltranslation-based,timeandlocationaware(TransTL)representation,whichmodelsthespatialandtemporalinformationasarelationshipconnectingusersandPOIs.Ourmodelgeneralizestherecentadvancesinknowledgegraphembedding.Thebasicideaisthattheembeddingofa〈time,location〉paircorrespondstoatranslationfromembeddingsofuserstoPOIs.SincethePOIembeddingshouldbeclosetotheuserembeddingplustherelationshipvector,therecommendationcanbeperformedbyselectingthetop-kPOIssimilartothetranslatedPOI,whichareallofthesametypeofobjects.Weconductextensiveexperimentsontworeal-worlddata.sets.TheresultsdemonstratethatourTransTLmodelachievesthestate-of-the-artperformance.Itisalsomuchmorerobusttodatasparsitythanthebaselines.
简介:Chinaisoneofthelargestcountriesintheworldintermsofplantedforestsarea.Plantedforestsplayanimportantroleinsoilandwaterconservation,foodsource,timbersupplyandenergysecurity,buttherearestillmanyproblemswaitingforimmediateresolution.BasedonthecurrentdevelopmentstatusofplantedforestinChina,thepapermadeancomprehensiveanalysisforthepositiveimpactandexistingproblemswithregardtoplantedforests,andthencameupwithpolicyrecommendationsforprom...
简介:在上面提到的由消费明星做的那些广告中,明星做广告,由消费明星把消费伦理宣扬得赤裸裸的莫过于王志文做的"派"牌服装广告
简介:在上面提到的由消费明星做的那些广告中,明星做广告,由消费明星把消费伦理宣扬得赤裸裸的莫过于王志文做的"派"牌服装广告
简介:在上面提到的由消费明星做的那些广告中,明星做广告,由消费明星把消费伦理宣扬得赤裸裸的莫过于王志文做的"派"牌服装广告
简介:1.IntroductionWiththeincreasingofturbo-generator(TG)capacity,thelimi-tationontheabnormalfrequencyoperationisgrowingmorerestric-tive.InordertoensurethesafetyoperationofcertainTGunit,splitingdevicewhichisolatesthegeneratingunitfromthesystemisem-ployedwhenthesystemfrequencyisdeclinedtoacertainextent.However,duringthedegradationoffrequency,toisolatethelarge-sizedTGunitfromthepowersystemwillcausethesystemfre-quencytofurtherdecline.Hence,howtousethelowfrequencysplit-tingprotectionproperlyandhowtocoordinatetheoperationofunderfrequencyloadshedding(UFLS)withunderfrequencygeneratorsplitting(UFGS)aresignificantforsecuringthesafetyoperationof
简介:最近的年见证网络(LBSN)满足的基于地点的聚会的曾经成长的流行。Top-N地方建议,瞄准检索呼吁为一个目标用户放的N大多数,因此获得了增加的重要性。这问题任何一个的然而存在的答案由选择附近流行的地方提供非个性化的建议,或诉诸合作过滤(CF)作为一个独立项目由各对待放,在地方之中俯看地理、语义的关联。在这篇论文,我们建议转到,提供top-N的合作recommender在LBSN个性化地方建议。与存在方法相比,转到由利用所谓的本地专家的智慧完成它的有效性,也就是,是的那些地理上关于某个用户关上并且有类似的偏爱。在转到谎言的核心,一项新奇用户类似措施叫了geo热门的类似,它为发现本地专家在地方之中联合地理、语义的关联。在里面特定,为用户建模的geo热门的类似使用Gaussian混合物真实地理模式,和摘录用户从历史上访问的地方的依附的标签的热门偏爱。真实LBSN数据集的广泛的实验证明与基线方法相比,转到能以精确性在多达50%改进top-N地方建议的性能。
简介:性健康或可勃起的机能障碍(编辑)现状指南提供常规药方或另外的著名外来的治疗的彻底的概述选择。在过去的10-15年,然而,国际研究人员的过多证实了单个、全面的生活方式变化能阻止并且潜在地改善我们考察的编辑应该等同分级A或为我们也考察的编辑铺平1个证据建议的生活方式证据为人参属人参的证据,一普通(OTC)有实验室调查,在约15年的多重积极使随机化的审判和几i的35年的历史的饮食的补充也许现在是至少在编辑指南讨论并且甚至强调生活方式和另外的非常规的干预以便病人们能探索的时间多种潜在地,与他们的医生和罐头一起的synergistic选择改进他们生活的质量和数量。例如,在编辑指南在生活方式修正上忽略一致、积极数据等于忽略食谱和生活方式变化减少风险或改善心血管的疾病。