Anonymity Published Study On Digital Library Information Services Platform

As databases,networks and information technologies make digital libraries have many users of digital information resources share platform,to provide users with convenient,varied and personalized service.Resource share and data publish not only to ensure the effectiveness and timeliness of the data,while not disclose individual information to safeguard individual privacy.The anonymous release of digital library information service platform is based on the premise of individual privacy security,maximize the use of individual information to generate safe and effective results of data analysis,and provide more users with secure and reliable information resource.The user information of digital library was particularity,use the specific data analysis methods are in specific areas to mining data to maximize the potential of information and ability to effectively protect data security.Through the analysis of existing research and anonymous model,this paper on digital library information services platform to study the anonymity of the data,the main tasks are as follows:(1)Digital Library user data anonymous publication.User data is an important component of the research and analysis of digital library data.In order to enable researchers to better study digital library data,it is necessary to publish data containing user attributes.Put forward a model of anonymity to retain user data,first of all user information screen conformity recode;then according to user data correlation to classify the users,by users;end connect user class and borrow information,we can get the mapping relation between user class and borrowing information,together anonymous publication.In addition,in view of the particularity of library information,it is transformed into numerical data,quantitative analysis is generated,and the data is visually analyzed by scatter diagram.To provide more valuable user information for researchers,data analysis is more comprehensive and safer.(2)Personalized anonymous publishing of digital library users.Personalized service is a premise of user selection,users set their hidden degree according to individual needs,so that users can subjectively affect the anonymity,and fully consider the individual needs of users.Put forward a method of personalized anonymity,first of all users set sensitivity to their attributes,at the same time set attribute weights based on degree of association between attribute,which constitute the user sensitive factors;secondly,user classes are classified according to sensitive factors,and personalized and anonymous publications are carried out.It provides the guarantee for the personalized service of digital library,meets the user's own settings,does not destroy the relationship between attributes,and better meet the needs of users.(3)Dynamic anonymous data publish digital libraries.Daily data of digital library will generate a lot of lending records,these borrowing records in a certain period of time may reflect some phenomena and problems,which need to update the dynamic data set,real-time reflect the lending records,more timeliness.In this paper,a dynamic anonymous publishing model is proposed to select the closest equivalence classes according to the calculated semantic proximity of each new data,and to update the tuples according to the anonymous conditions,so as to achieve dynamic real-time updating.With original model is not destroyed to update,ensure anonymous data in real time and reduce the delay of information.(4)Digital library information services platform.The existing digital libraries lack data analysis information,only publish books information and related borrowing frequency information,the user attributes and attribute library released together,the library can provide more comprehensive information for related research in order to facilitate the analysis,so the establishment of data integration management of the digital library publishing platform.In this information service platform,not only the anonymous data is published,but also the data mining techniques such as association rules and cluster analysis are used to analyze the anonymous data to provide users with more intuitive analysis results.It makes users have more detailed attributes,classification,selection and reference opinions in selecting books,and improves the service quality of digital library information service platform as a whole.This paper studies the digital library user data anonymity,detailed analysis of the algorithm and the detailed experiments combined with the actual data set,the test and performance analysis show that this algorithm has good performance and practical ability.