Meaningful Integration in Professional Communities: Examining User Behaviors in Catalyst

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Stephanie W. P. Knight ◽  
Julie M. Sykes ◽  
Linda Forrest ◽  
Carla H. Consolini ◽  
Johanna Jimenez
2021 ◽  
Vol 285 ◽  
pp. 116429
Author(s):  
Wen-Long Shang ◽  
Jinyu Chen ◽  
Huibo Bi ◽  
Yi Sui ◽  
Yanyan Chen ◽  
...  

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.


2020 ◽  
Vol 44 (1) ◽  
pp. 72-79
Author(s):  
Nathalie Marcerou-Ramel

AbstractFrance is probably the only European country to have today a national school for training of library and information professionals: Enssib, National Library and Information Science School. An atypical situation, as some countries decided to close their schools of librarianship and entrust the training of their professionals to universities only. How does Enssib train its library executives? The article first describes the recruitment, training and exercise framework for French library and information professionals. Then it focuses on the vast renovation project that Enssib has been launching for four years in order to adapt its training processes to the needs and expectations of the professional communities.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4212
Author(s):  
Priscila Morais Argôlo Bonfim Estrela ◽  
Robson de Oliveira Albuquerque ◽  
Dino Macedo Amaral ◽  
William Ferreira Giozza ◽  
Rafael Timóteo de Sousa Júnior

As smart devices have become commonly used to access internet banking applications, these devices constitute appealing targets for fraudsters. Impersonation attacks are an essential concern for internet banking providers. Therefore, user authentication countermeasures based on biometrics, whether physiological or behavioral, have been developed, including those based on touch dynamics biometrics. These measures take into account the unique behavior of a person when interacting with touchscreen devices, thus hindering identitification fraud because it is hard to impersonate natural user behaviors. Behavioral biometric measures also balance security and usability because they are important for human interfaces, thus requiring a measurement process that may be transparent to the user. This paper proposes an improvement to Biotouch, a supervised Machine Learning-based framework for continuous user authentication. The contributions of the proposal comprise the utilization of multiple scopes to create more resilient reasoning models and their respective datasets for the improved Biotouch framework. Another contribution highlighted is the testing of these models to evaluate the imposter False Acceptance Error (FAR). This proposal also improves the flow of data and computation within the improved framework. An evaluation of the multiple scope model proposed provides results between 90.68% and 97.05% for the harmonic mean between recall and precision (F1 Score). The percentages of unduly authenticated imposters and errors of legitimate user rejection (Equal Error Rate (EER)) are between 9.85% and 1.88% for static verification, login, user dynamics, and post-login. These results indicate the feasibility of the continuous multiple-scope authentication framework proposed as an effective layer of security for banking applications, eventually operating jointly with conventional measures such as password-based authentication.


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