中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An incremental model on search engine query recommendation

文献类型:期刊论文

作者JianGuo Wang; Joshua Zhexue Huang; Dingming Wu; JiaFeng Guo; Yanyan Lan
刊名Neurocomputing
出版日期2016
英文摘要Search enginequeryrecommendationbasedonminingquerylogshasbeenconsideredasanimportant and usefulmethodoffacilitatinguserstoretrieveinformation.However,thelogdataevolvesquickly. Existing queryrecommendationapproacheshavetorebuildthemodelswhennewlogdataarrive.Inthis paper,weextendthequeryrankingmodel(QRM)proposedinourpreviouswork(Wangetal.,2015) [1] to anadaptivemodelinwhichnewcominglogdataisincrementallyadded,sothattherecommendation model iskeptup-to-date.Theexperimentalresultshavedemonstratedthattheproposedincremental queryrankingmodel(IQRM)isabletorecommendqueriesmoreefficiently thanre-buildingQRMon evolvinglogdatawithoutlosingaccuracy.
收录类别SCI
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/10274]  
专题深圳先进技术研究院_数字所
作者单位Neurocomputing
推荐引用方式
GB/T 7714
JianGuo Wang,Joshua Zhexue Huang,Dingming Wu,et al. An incremental model on search engine query recommendation[J]. Neurocomputing,2016.
APA JianGuo Wang,Joshua Zhexue Huang,Dingming Wu,JiaFeng Guo,&Yanyan Lan.(2016).An incremental model on search engine query recommendation.Neurocomputing.
MLA JianGuo Wang,et al."An incremental model on search engine query recommendation".Neurocomputing (2016).

入库方式: OAI收割

来源:深圳先进技术研究院

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。