{"title":"个性化信息检索中用户偏好隐私保护:挑战与综述","authors":"Zongda Wu, Chenglang Lu, Youlin Zhao, Jian Xie, Dongdong Zou, Xinning Su","doi":"10.1515/libri-2019-0140","DOIUrl":null,"url":null,"abstract":"Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.","PeriodicalId":45618,"journal":{"name":"Libri-International Journal of Libraries and Information Studies","volume":"71 1","pages":"227 - 237"},"PeriodicalIF":0.8000,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/libri-2019-0140","citationCount":"8","resultStr":"{\"title\":\"The Protection of User Preference Privacy in Personalized Information Retrieval: Challenges and Overviews\",\"authors\":\"Zongda Wu, Chenglang Lu, Youlin Zhao, Jian Xie, Dongdong Zou, Xinning Su\",\"doi\":\"10.1515/libri-2019-0140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.\",\"PeriodicalId\":45618,\"journal\":{\"name\":\"Libri-International Journal of Libraries and Information Studies\",\"volume\":\"71 1\",\"pages\":\"227 - 237\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2021-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1515/libri-2019-0140\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Libri-International Journal of Libraries and Information Studies\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1515/libri-2019-0140\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Libri-International Journal of Libraries and Information Studies","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1515/libri-2019-0140","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
The Protection of User Preference Privacy in Personalized Information Retrieval: Challenges and Overviews
Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.
期刊介绍:
Libri, International Journal of Libraries and Information Services, investigates the functions of libraries and information services from both a historical and present-day perspective and analyses the role of information in cultural, organizational, national and international developments. The periodical reports on current trends in librarianship worldwide and describes the transformation of libraries and information services resulting from the introduction of new information technologies and working methods. Background information and the latest research findings in librarianship and information science are made accessible to experts and a broader public. Articles are in English and conform to the highest academic standards.