{"title":"Authenticating Preference-Oriented Multiple Users Spatial Queries","authors":"Xiaoran Duan, Yong Wang, Juguang Chen, Junhao Zhang","doi":"10.1109/COMPSAC.2017.68","DOIUrl":null,"url":null,"abstract":"Location-based social networks (LBSNs) are attracting significant attentions, which make location-aware applications prosperous. We proposed the Multiple User-defined Spatial Query (MUSQ) in [1]. However, it is impractical that non-expert users provide exact vectors to denote their preferences in MUSQ. In this paper, we design a group users weight matrix generation algorithm to represent users' preferences conveniently. In addition, we propose a refinement method to improve the effectiveness of the query results. Further, considering the trust issue introduced by data outsourcing, an authenticated query processing framework is proposed. A set of experiments are conducted to show the effectiveness and scalability of our methods under various parameter settings.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"15 1","pages":"602-607"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSAC.2017.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Location-based social networks (LBSNs) are attracting significant attentions, which make location-aware applications prosperous. We proposed the Multiple User-defined Spatial Query (MUSQ) in [1]. However, it is impractical that non-expert users provide exact vectors to denote their preferences in MUSQ. In this paper, we design a group users weight matrix generation algorithm to represent users' preferences conveniently. In addition, we propose a refinement method to improve the effectiveness of the query results. Further, considering the trust issue introduced by data outsourcing, an authenticated query processing framework is proposed. A set of experiments are conducted to show the effectiveness and scalability of our methods under various parameter settings.
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