The protection of personal information plays an extremely important role in the construction of digital government.The duty to inform is a prerequisite core obligation that the government should fulfill in processing ...The protection of personal information plays an extremely important role in the construction of digital government.The duty to inform is a prerequisite core obligation that the government should fulfill in processing personal information,a concrete expression of the right to self-determination of personal information,and a prerequisite for the right to protection of personal information that works as a fundamental right to defense the intrusion from the government,as well as a procedural regulatory tool to restrain the government’s information power and prevent the risk of infringement.As the rules on the processing of personal information and the duty to inform have both the nature of public law,the government’s processing of personal information is also public law in nature,especially because of the constitutional value and power control function of the duty to inform,the construction of a system for the duty to inform cannot be copied from the rules applicable to private subjects,but should be tailored to the public law characteristics of the government’s processing of personal information,overcoming the shortcomings of the current rough and fragmented legislation,and set up a systematic regulation based on the public law in term of the legal subject,procedure,content,consequences of obligation violations and legal protection.展开更多
Personally identifiable information(PII)refers to any information that links to an individual.Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations.Buildin...Personally identifiable information(PII)refers to any information that links to an individual.Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations.Building a PII retrieval service over multi-cloud,which is a modern strategy to make services stable where multiple servers are deployed,seems to be a promising solution.However,three major technical challenges remain to be solved.The first is the privacy and access control of PII.In fact,each entry in PII can be shared to different users with different access rights.Hence,flexible and fine-grained access control is needed.Second,a reliable user revocation mechanism is required to ensure that users can be revoked efficiently,even if few cloud servers are compromised or collapse,to avoid data leakage.Third,verifying the correctness of received PII and locating a misbehaved server when wrong data are returned is crucial to guarantee user’s privacy,but challenging to realize.In this paper,we propose Rainbow,a secure and practical PII retrieval scheme to solve the above issues.In particular,we design an important cryptographic tool,called Reliable Outsourced Attribute Based Encryption(ROABE)which provides data privacy,flexible and fine-grained access control,reliable immediate user revocation and verification for multiple servers simultaneously,to support Rainbow.Moreover,we present how to build Rainbow with ROABE and several necessary cloud techniques in real world.To evaluate the performance,we deploy Rainbow on multiple mainstream clouds,namely,AWS,GCP and Microsoft Azure,and experiment in browsers on mobile phones and computers.Both theoretical analysis and experimental results indicate that Rainbow is secure and practical.展开更多
A new method to evaluate fuzzily user＇s relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method f...A new method to evaluate fuzzily user＇s relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval （PIR） system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.展开更多
Over the years, there has been increasing growth in academic digital libraries. It has therefore become overwhelming for researchers to determine important research materials. In most existing research works that cons...Over the years, there has been increasing growth in academic digital libraries. It has therefore become overwhelming for researchers to determine important research materials. In most existing research works that consider scholarly paper recommendation, the researcher’s preference is left out. In this paper, therefore, Frequent Pattern (FP) Growth Algorithm is employed on potential papers generated from the researcher’s preferences to create a list of ranked papers based on citation features. The purpose is to provide a recommender system that is user oriented. A walk through algorithm is implemented to generate all possible frequent patterns from the FP-tree after which an output of ordered recommended papers combining subjective and objective factors of the researchers is produced. Experimental results with a scholarly paper recommendation dataset show that the proposed method is very promising, as it outperforms recommendation baselines as measured with nDCG and MRR.展开更多
With the popularity of mobile intelligent terminal, user comments of App software is viewed as one of the research interests of social computing. Faced with the massive App software, most users usually view the other ...With the popularity of mobile intelligent terminal, user comments of App software is viewed as one of the research interests of social computing. Faced with the massive App software, most users usually view the other users’ comments and marks to selecting the desired App software. Due to the freedom and randomness of the network comments, the inconsistence between the user’s comment and mark makes it difficult to choose App software. This paper presents a method by analyzing the relationships among user’s comment information, the user’s mark and App software information. Firstly, the consistency between user’s comment information and App software information is judged. Then, through analyzing the grammar relationships among the feature-words, adverbs and the feature-sentiment-words in App software’s feature-sentimentword- pairs, the user’s emotional tendency about App software is quantified quantified combining with the dictionary and the network sentiment words. After calculating the user’s comprehensive score of App software, the consistency of App software’s user comment is judged by comparing this score and the user’s mark. Finally, the experimental results show that the method is effective.展开更多
文摘The protection of personal information plays an extremely important role in the construction of digital government.The duty to inform is a prerequisite core obligation that the government should fulfill in processing personal information,a concrete expression of the right to self-determination of personal information,and a prerequisite for the right to protection of personal information that works as a fundamental right to defense the intrusion from the government,as well as a procedural regulatory tool to restrain the government’s information power and prevent the risk of infringement.As the rules on the processing of personal information and the duty to inform have both the nature of public law,the government’s processing of personal information is also public law in nature,especially because of the constitutional value and power control function of the duty to inform,the construction of a system for the duty to inform cannot be copied from the rules applicable to private subjects,but should be tailored to the public law characteristics of the government’s processing of personal information,overcoming the shortcomings of the current rough and fragmented legislation,and set up a systematic regulation based on the public law in term of the legal subject,procedure,content,consequences of obligation violations and legal protection.
基金This work was supported by National Natural Science Foundation of China(Nos.62172411,62172404,61972094)。
文摘Personally identifiable information(PII)refers to any information that links to an individual.Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations.Building a PII retrieval service over multi-cloud,which is a modern strategy to make services stable where multiple servers are deployed,seems to be a promising solution.However,three major technical challenges remain to be solved.The first is the privacy and access control of PII.In fact,each entry in PII can be shared to different users with different access rights.Hence,flexible and fine-grained access control is needed.Second,a reliable user revocation mechanism is required to ensure that users can be revoked efficiently,even if few cloud servers are compromised or collapse,to avoid data leakage.Third,verifying the correctness of received PII and locating a misbehaved server when wrong data are returned is crucial to guarantee user’s privacy,but challenging to realize.In this paper,we propose Rainbow,a secure and practical PII retrieval scheme to solve the above issues.In particular,we design an important cryptographic tool,called Reliable Outsourced Attribute Based Encryption(ROABE)which provides data privacy,flexible and fine-grained access control,reliable immediate user revocation and verification for multiple servers simultaneously,to support Rainbow.Moreover,we present how to build Rainbow with ROABE and several necessary cloud techniques in real world.To evaluate the performance,we deploy Rainbow on multiple mainstream clouds,namely,AWS,GCP and Microsoft Azure,and experiment in browsers on mobile phones and computers.Both theoretical analysis and experimental results indicate that Rainbow is secure and practical.
文摘A new method to evaluate fuzzily user＇s relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval （PIR） system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.
文摘Over the years, there has been increasing growth in academic digital libraries. It has therefore become overwhelming for researchers to determine important research materials. In most existing research works that consider scholarly paper recommendation, the researcher’s preference is left out. In this paper, therefore, Frequent Pattern (FP) Growth Algorithm is employed on potential papers generated from the researcher’s preferences to create a list of ranked papers based on citation features. The purpose is to provide a recommender system that is user oriented. A walk through algorithm is implemented to generate all possible frequent patterns from the FP-tree after which an output of ordered recommended papers combining subjective and objective factors of the researchers is produced. Experimental results with a scholarly paper recommendation dataset show that the proposed method is very promising, as it outperforms recommendation baselines as measured with nDCG and MRR.
基金This research is sponsored by the National Science Foundation of China No. 60703116, 61063006 and 61462049, and the Application Basic Research Plan in Yunnan Province of China No. 2013FZ020.
文摘With the popularity of mobile intelligent terminal, user comments of App software is viewed as one of the research interests of social computing. Faced with the massive App software, most users usually view the other users’ comments and marks to selecting the desired App software. Due to the freedom and randomness of the network comments, the inconsistence between the user’s comment and mark makes it difficult to choose App software. This paper presents a method by analyzing the relationships among user’s comment information, the user’s mark and App software information. Firstly, the consistency between user’s comment information and App software information is judged. Then, through analyzing the grammar relationships among the feature-words, adverbs and the feature-sentiment-words in App software’s feature-sentimentword- pairs, the user’s emotional tendency about App software is quantified quantified combining with the dictionary and the network sentiment words. After calculating the user’s comprehensive score of App software, the consistency of App software’s user comment is judged by comparing this score and the user’s mark. Finally, the experimental results show that the method is effective.
