%0 Journal Article
%T 文献推荐系统：提高信息检索效率之途
%A 刘婧婧
%A 张向民
%J 图书情报工作
%D 2007
%X ？traditionalinformationretrieval(ir)systemshavelimitationsinimprovingsearchperformanceintoday’sinformationenvironment.thehighrecallandpoorprecisionoftraditionalirsystemsareonlyasgoodaswiththeaccuracyofsearchquery,whichis,however,usuallydifficultfortheusertoconstruct.itisalsotime-consumingfortheusertoevaluateeachsearchresult.therecommendationtechniqueshavingbeendevelopedsincetheearly1990shelpsolvetheproblemsthattraditionalirsystemshave.thispaperexplainsthebasicprocessandmajorelementsofdocumentrecommendersystems,especiallythetworecommendationtechniquesofcontent-basedfilteringandcollaborativefiltering.alsodiscussedaretheevaluationissueandtheproblemsthatcurrentdocumentrecommendersystemsarefacing,whichneedtobetakenintoaccountinfuturesystemdesigns.traditionalinformationretrieval(ir)systemshavelimitationsinimprovingsearchperformanceintoday’sinformationenvironment.thehighrecallandpoorprecisionoftraditionalirsystemsareonlyasgoodaswiththeaccuracyofsearchquery,whichis,however,usuallydifficultfortheusertoconstruct.itisalsotime-consumingfortheusertoevaluateeachsearchresult.therecommendationtechniqueshavingbeendevelopedsincetheearly1990shelpsolvetheproblemsthattraditionalirsystemshave.thispaperexplainsthebasicprocessandmajorelementsofdocumentrecommendersystems,especiallythetworecommendationtechniquesofcontent-basedfilteringandcollaborativefiltering.alsodiscussedaretheevaluationissueandtheproblemsthatcurrentdocumentrecommendersystemsarefacing,whichneedtobetakenintoaccountinfuturesystemdesigns.
%U http://124.16.154.130:8080/lis/CN/abstract/abstract8591.shtml