Is adaptation of e-advertising the way forward?

E-advertising is a multi-billion dollar industry that has shown exponential growth in the last few years. However, although the number of users accessing the Internet increases, users don’t respond positively to adverts. Adaptive e-advertising may be the key to ensuring effectiveness of the ads reaching their target. Moreover, social networks are good sources of user information and can be used to extract user behaviour and characteristics for presentation of personalized advertising. Here we present a two-sided study based on two questionnaires, one directed to Internet users and the other to businesses. Our study shows that businesses agree that personalized advertising is the best way for the future, to maximize effectiveness and profit. In addition, our results indicate that most Internet users would prefer adaptive advertisements. From this study, we can propose a new design for a system that meets both Internet users’ and businesses’ requirements

Boundary energy of the open XXZ chain from new exact solutions

Bethe Ansatz solutions of the open spin-1/2 integrable XXZ quantum spin chain at roots of unity with nondiagonal boundary terms containing two free boundary parameters have recently been proposed. We use these solutions to compute the boundary energy (surface energy) in the thermodynamic limit.Comment: 20 pages, LaTeX; amssymb, 3 figure

Investigating the impact of social interactions in adaptive E-Learning by learning behaviour analysis

Adaptive Educational Hypermedia Systems (AEHSs) allow for personalization of e-learning1 . Social media tools enable learners to create, publish and share their study, and facilitate interaction and collaboration2 . The integration of social media tools into AEHS offers novel opportunities for learner engagement and extended user modelling, and thereby fosters so-called Social Personalized Adaptive E-learning Environments (SPAEEs) 3. However, there has been a lack of empirical design and evaluation to elaborate methods for SPAEEs. The goal of research, therefore, is to investigate 1) the learning behaviour patterns within SPAEEs and the use of these patterns for learner engagement, 2) the evaluation methodologies for SPAEEs, and 3) the design principles for SPAEEs. Topolor4 is a SPAEE that has been under iterative development for achieving our research goals. The first prototype was used as an online learning system for MSc level students in the Department of Computer Science, at the University of Warwick, and usage data was anonymously collected for analysis5 . This poster focuses on system features and learning behaviour analysis. We firstly present the methodologies applied in the research, followed by the social and adaptive features that Topolor provides6 . Then we revisit the analysis of learning behaviours7 . Finally we propose the follow-up work based on the evaluation results

Designing social personalized adaptive e-learning

Here we introduce Topolor, a social personalized adaptive elearning system aiming to improve social interaction in the learning process as well as applying classical adaptation based on user modeling. Here, we focus on the system architecture and preliminary evaluation that showed high system usability