A privacy-preserving recommendation method based on multi-objective optimisation for mobile users

Xu, Chonghuan; Ding, Austin Shijun; Liao, Stephen Shaoyi

doi:10.1504/ijbic.2020.108995

Cited by 21 publications

(11 citation statements)

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“…The next stage will study the interaction between individuals at the micro level in the context of the spread of epidemic rumors. In the future, the research results can be applied into various fields including personalized recommendation ( 33 – 35 ), anomaly detection ( 36 , 37 ), sustainable tourism ( 38 , 39 ), personal health ( 40 ), and so on.…”

Section: Discussionmentioning

confidence: 99%

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19

Jiang

Bao

et al. 2022

Front. Public Health

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In the era of mobile internet, information dissemination has made a new leap in speed and in breadth. With the outbreak of the coronavirus disease 2019 (COVID-19), the COVID-19 rumor diffusion that is not limited by time and by space often becomes extremely complex and fickle. It is also normal that a piece of unsubstantiated news about COVID-19 could develop to many versions. We focus on the stagnant role and information variants in the process of rumor diffusion about COVID-19, and through the study of variability and silence in the dissemination, which combines the effects of stagnation phenomenon and information variation on the whole communication system in the circulation of rumors about COVID-19, based on the classic rumor SIR (Susceptible Infected Recovered) model, we introduce a new concept of “variation” and “oyster”. The stability of the new model is analyzed by the mean field equation, and the threshold of COVID-19 rumor propagation is obtained later. According to the results of the simulation experiment, whether in the small world network or in the scale-free network, the increase of the immure and the silent probability of the variation can effectively reduce the speed of rumor diffusion about COVID-19 and is conducive to the dissemination of the truth in the whole population. Studies have also shown that increasing the silence rate of variation can reduce COVID-19 rumor transmission more quickly than the immunization rate. The interesting discovery is that at the same time, a higher rumor infection rate can bring more rumors about COVID-19 but does not always maintain a high number of the variation which could reduce variant tendency of rumors. The more information diffuses in the social group, the more consistent the version and content of the information will be, which proves that the more adequate each individual information is, the slower and less likely rumors about COVID-19 spread. This consequence tells us that the government needs to guide the public to the truth. Announcing the true information publicly could instantly contain the COVID-19 rumor diffusion well rather than making them hidden or voiceless.

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Section: Discussionmentioning

confidence: 99%

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19

Jiang

Bao

et al. 2022

Front. Public Health

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“…This paper studies the variations and oysters in network communication and puts forward a new transmission mechanism and introduces the phenomenon of stagnation and information mutation in the network. The model has a wide range of application scenarios in the future, including personalized recommendation [40][41][42][43], data processing [44][45][46], sustainable tourism [47,48], knowledge dissemination [49] and so on. At the same time, there are still some limitations, for example, although the parameters of this paper were obtained after the simulation of actual cases, it is not considered in the later analysis that the parameters will change dynamically according to the development of actual events [50].…”

Section: Discussionmentioning

confidence: 99%

Exploring a Multi-Layer Coupled Network Propagation Model Based on Information Diffusion and Bounded Trust

Ju¹,

Wang²,

Jiang³

et al. 2022

Int J Public Health

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Objective: To explore the law of opinion dissemination and individual opinion evolution at the micro level, this paper analyzes the influence of variation and oyster on communication from the perspective of network structure.Methods: In this paper, we introduce the concepts of “variation” and “oyster”, build a multi-layer coupled network environment combined with the ISOVR model, and conduct simulation experiments of network information dissemination based on the bounded trust model.Results: The experimental results reveal that the extent and scope of variation’s spread in the network are more dependent on the trust of nodes themselves, and decreasing the trust of nodes significantly reduces the rate and peak value of variation. Changing the silence coefficient of variation does not effectively change the direction of rumor propagation, which indicates that rumor has a strong propagation ability after mutation.Conclusion: The insights of this paper on the dissemination of public opinions include: 1) pay attention to people with high trust levels, such as opinion leaders; 2) clarify the misinformation in time to prevent further spread of rumors.

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“…In recent years, information privacy of people has gradually become the focus of scholars [34]. Similarly, the information privacy of data in the field of skin cancer research has become a top priority.…”

Section: The Federated Skin Cancer Detection Model Based On Many-obje...mentioning

confidence: 99%

A many-objective evolutionary algorithm based on integrated strategy for skin cancer detection

2022

KSII TIIS

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Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.

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A privacy-preserving recommendation method based on multi-objective optimisation for mobile users

Cited by 21 publications

References 0 publications

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19

Exploring a Multi-Layer Coupled Network Propagation Model Based on Information Diffusion and Bounded Trust

A many-objective evolutionary algorithm based on integrated strategy for skin cancer detection

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