The paper investigates the role of user bias in online trust systems and develops a methodology for the design of better systems. It delves into the workings of online computational trust systems under user bias and analyses the user behaviour through biases defined by Prospect theory. The results of an empirical study and the analysis are used to propose to the system designers a methodology for user bias identification and mitigation for trust systems based on the subjective logic theory, which reduces complexity and improves the user experience and the system performance.
COBISS.SI-ID: 29835815
For firms, consumer satisfaction is an important indicator of e-commerce success. Today, consumers' reviews and feedback are increasingly shaping consumer intentions regarding new purchases and repeated purchases, while helping to attract new customers. In the article an expert system is used to predict the user sentiment to a product considering a subset of available customers' reviews.
COBISS.SI-ID: 23780582
The study analyses the phenomena of additiction and abuse in the working environment in Slovenia and provides empirical results regarding the electronic monitoring of the employees and the respective consequences.
COBISS.SI-ID: 30885159
Vectorial Boolean bent functions, which possess the maximal nonlinearity and the minimum differential uniformity, contribute to optimum resistance against linear cryptanalysis and differential cryptanalysis for the cryptographic algorithms that adopt them as nonlinear components. The maximum number of these functions is calculated in the article as an important data in designing Boolean based crypto systems that are resisting several types of crypto-analysis.
COBISS.SI-ID: 30989863
The re-design of an internet service was carried out by the input collected from a study of specifiv group of virtual users with demanding requirements. The results of the study and the re-designed service were used for definition of recommendations for acting in similar cases.
COBISS.SI-ID: 30544679