Why bernstein polynomials are better: Fuzzy-inspired justification

Nava, Jaime; Kosheleva, Olga; Kreinovich, Vladik

doi:10.1109/fuzz-ieee.2012.6251341

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Others have suggested the use of the Bernstein polynomial in the estimation problem. Nava et al [21] proved that the Bernstein polynomial is more efficient in a computational manner, is universal, and is dominant in computation time compared with traditional polynomials. Hence, this approach has been applied to measure the sensitivity of information in the study and works well in approximation.…”

Section: Related Workmentioning

confidence: 99%

A Privacy-Enhanced Friending Approach for Users on Multiple Online Social Networks

2018

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Online social network users share their information in different social sites to establish connections with individuals with whom they want to be a friend. While users share all their information to connect to other individuals, they need to hide the information that can bring about privacy risks for them. As user participation in social networking sites rises, the possibility of sharing information with unknown users increases, and the probability of privacy breaches for the user mounts. This work addresses the challenges of sharing information in a safe manner with unknown individuals. Currently, there are a number of available methods for preserving privacy in order to friending (the act of adding someone as a friend), but they only consider a single source of data and are more focused on users’ security rather than privacy. Consequently, a privacy-preserving friending mechanism should be considered for information shared in multiple online social network sites. In this paper, we propose a new privacy-preserving friending method that helps users decide what to share with other individuals with the reduced risk of being exploited or re-identified. In this regard, the first step is to calculate the sensitivity score for individuals using Bernstein’s polynomial theorem to understand what sort of information can influence a user’s privacy. Next, a new model is applied to anonymise the data of users who participate in multiple social networks. Anonymisation helps to understand to what extent a piece of information can be shared, which allows information sharing with reduced risks in privacy. Evaluation indicates that measuring the sensitivity of information besides anonymisation provides a more accurate outcome for the purpose of friending, in a computationally efficient manner.

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Section: Related Workmentioning

confidence: 99%

A Privacy-Enhanced Friending Approach for Users on Multiple Online Social Networks

2018

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“…This explanation first appeared in [103]. To provide the desired intuitive explanation, we use fuzzy logic-a technique for describing informal intuitive arguments.…”

Section: Preliminarymentioning

confidence: 99%

Algorithmic Aspects of Analysis, Prediction, and Control in Science and Engineering

Nava¹,

Kreinovich²

2015

Studies in Systems, Decision and Control

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The series "Studies in Systems, Decision and Control" (SSDC) covers both new developments and advances, as well as the state of the art, in the various areas of broadly perceived systems, decision making and control-quickly, up to date and with a high quality. The intent is to cover the theory, applications, and perspectives on the state of the art and future developments relevant to systems, decision making, control, complex processes and related areas, as embedded in the fields of engineering, computer science, physics, economics, social and life sciences, as well as the paradigms and methodologies behind them. The series contains monographs, textbooks, lecture notes and edited volumes in systems, decision making and control spanning the areas of Cyber-Physical SystemsSocial Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output.More information about this series at

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Adaptive Bezier Curve-based Membership Function formulation scheme for Interpretable Edge Detection

Madhu

Shet

2023

Applied Soft Computing

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Why bernstein polynomials are better: Fuzzy-inspired justification

Cited by 3 publications

References 7 publications

A Privacy-Enhanced Friending Approach for Users on Multiple Online Social Networks

A Privacy-Enhanced Friending Approach for Users on Multiple Online Social Networks

Algorithmic Aspects of Analysis, Prediction, and Control in Science and Engineering

Adaptive Bezier Curve-based Membership Function formulation scheme for Interpretable Edge Detection

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