Engaging end-user driven recommender systems: personalization through web augmentation

In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations of items into arbitrary websites on client-side. For this we have developed a generic meta-model to capture recommender system configuration parameters in general as well as in a web augmentation context. Thereupon, we have implemented a wizard in the form of an easy-to-use browser plug-in, allowing the generation of so-called user scripts, which are executed in the browser to engage collaborative filtering functionality from a provided external rest service. We discuss functionality and limitations of the approach, and in a study with end-users we assess the usability and show its suitability for combining recommender systems with web augmentation techniques, aiming to empower end-users to implement controllable recommender applications for a more personalized browsing experience.

An End User Development Approach for Mobile Web Augmentation

The trend towards mobile devices usage has made it possible for the Web to be conceived not only as an information space but also as a ubiquitous platform where users perform all kinds of tasks. In some cases, users access the Web with native mobile applications developed for well-known sites, such as, LinkedIn, Facebook, and Twitter. These native applications might offer further (e.g., location-based) functionalities to their users in comparison with their corresponding Web sites because they were developed with mobile features in mind. However, many Web applications have no native counterpart and users access them using a mobile Web browser. Although the access to context information is not a complex issue nowadays, not all Web applications adapt themselves according to it or diversely improve the user experience by listening to a wide range of sensors. At some point, users might want to add mobile features to these Web sites, even if those features were not originally supported. In this paper, we present a novel approach to allow end users to augment their preferred Web sites with mobile features.We support our claims by presenting a framework for mobile Web augmentation, an authoring tool, and an evaluation with 21 end users.