The trend towards mobile devices usage has put more than ever the Web as a ubiquitous platform where users perform all kind of tasks. In some cases, users access the Web with "native" mobile applications developed for well-known sites, such as LinkedIn, Facebook, Twitter, etc. 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, most Web applications have not this native mobile counterpart and users access them using browsers in the mobile device. Users might eventually want to add mobile features on these Web sites even though those features were not supported originally. In this paper we present a novel approach to allow end users to augment their preferred Web sites with mobile features. This end-user approach is supported by a framework for mobile Web augmentation that we describe in the paper. We also present a set of supporting tools and a validation experiment with end users.

Building Mobile Web or Hypermedia Applications is usually difficult since there is a myriad of issues to take into account. Moreover adding support for personalized or context-aware behaviors goes far beyond the possibilities of many kinds of organizations that intend to build this kind of software (museums, city halls, etc). In this article we present a novel approach to delegate part of the effort in building mobile Web software to developers outside those organizations or even to final users. We show that this approach is feasible, light and practical and present a set of experiments we developed to verify our claims.

The World Wide Web is a vast and continuously changing source of information where searching is a frequent, and sometimes critical, user task. Searching is not always the user's primary goal but an ancillary task that is performed to find complementary information allowing to complete another task. In this paper, we explore primary and/or ancillary search tasks and propose an approach for simplifying the user interaction during search tasks. Rather than focusing on dedicated search engines, our approach allows the user to abstract search engines already provided by Web applications into pervasive search services that will be available for performing searches from any other Web site. We also propose to allow users to manage the way in which searching results are displayed and the interaction with them. In order to illustrate the feasibility of this approach, we have built a support tool based on a plug-in architecture that allows users to integrate new search services (created by themselves by means of visual tools) and execute them in the context of both kinds of searches. A case study illustrates the use of these tools. We also present the results of two evaluations that demonstrate the feasibility of the approach and the benefits in its use.

In this paper we present a user experience report on a Group Decision Support System. The used system is a Collaborative framework called GRoUp Support (GRUS). The experience consists in three user tests conducted in three different countries. While the locations are different, all three tests were run in the same conditions: same facilitator and tested process. In order to support the end-users. we teach the system in two different ways: a presentation of the system, and a video demonstrating how to use it. The main feedback of this experience is that the teaching step for using Collaborative tools in mandatory. The experience was conducted in the context of decision-making in the agriculture domain.

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.