A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Geethalakshmi, K.
- Privacy Risks in Recommender Systems
Authors
1 Department of BCA, PSGR Krishnammal College for Women, Coimbatore- 641 004, IN
2 Department of Computer Science, PSGR Krishnammal College for Women, Coimbatore- 641 004, IN
Source
Biometrics and Bioinformatics, Vol 5, No 12 (2013), Pagination: 417-424Abstract
In many on-line applications, the range of content that is offered to users is so wide that a requirement for automatic recommender systems arises. Such systems will give a personalized selection of relevant things to users. In practice, this may facilitate people realize fun movies, boost sales through targeted advertisements, or facilitate social network users meet new friends.
To produce correct personalized recommendations, recommender systems depend on detailed personal information on the preferences of users. Ratings, consumption histories and personal profiles are examples. Recommender systems are useful, but the privacy risks associated in aggregation and process personal information are typically underestimated or neglected. Many users are not sufficiently aware if and the way a lot of their information is collected, if such information is sold-out to third parties or how securely it is saved and for how long.
This paper aims to provide insight into privacy in recommender systems. First, we shall discuss different varieties of existing recommender systems. Second, an overview of the data that is employed in recommender systems is given. Third, I analyze the associated risks to information privacy. Finally, relevant research areas for privacy-protection techniques and their relevancy to recommender systems are mentioned.
Keywords
Recommender Systems, Privacy Risks, Privacy, Privacy-Protection Techniques.
- Cloud Computing, Big Data and the Industry 4.0
Authors
1 Department of BCA, PSGR Krishnammal College for Women, Coimbatore,, IN
2 Department of BCA, PSGR Krishnammal College for Women, Coimbatore., IN
Source
Software Engineering, Vol 13, No 1 (2021), Pagination: 15-18Abstract
The Industry 4.0 promotes the use of Information and Communication Technologies (ICT) in manufacturing processes to obtain customized products satisfying demanding needs of new consumers. The Industry 4.0 approach transforms the traditional pyramid model of automation to a network model of interconnected services, combining Operational Technology (OT) with Information Technology (IT). This new model allows the creation of ecosystems enabling more flexible production processes through connecting systems and sharing data. In this context, cloud computing and big data are critical technologies for leveraging the approach. Thus, this paper analyzes cloud computing and big data under the lenses of two leading reference architectures for implementing Industry 4.0: 1) the Industrial Internet Reference Architecture (IIRA), and 2) the Reference Architecture Model Industrie 4.0 (RAMI 4.0). A main contribution of this paper is to discussing needs, benefits, and challenges of applying cloud computing and big data in the Industry 4.0.Keywords
Big Data, Cloud Computing, Industry 4.0, Industrial Internet Reference Architecture (IIRA), Reference Architecture Model Industrie 4.0 (RAMI 4.0).References
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