Knowledge Producing Megamachines

In the present study, the authors point of departure is the control crisis of science whose resolution requires radical social innovation. The author then shows that the only possible way for achieving this is the partial fusion of certain portions of scientific activity with the system of public education, by means of organizing scientists, teachers, as well as middle and high-school students into hybrid, knowledge producing mega-machines. The author shall subsequently argue that doing so will at the same time bring about a pragmatic shift in public education, for which professionals in the field of pedagogy have long been ready in principle and in theory. As a final result we shall see the emergence of science and public instruction tailored to the global system level, within the framework of the information society.

Explaining Semantic Web Applications

In this chapter, we introduce the concept of explanation for Semantic Web applications by providing motivation, description, and examples. We describe the Inference Web explanation toolkit that provides support for a broad range of explanation tasks ranging from explaining deductive reasoning, to information extraction, to hybrid integrated learning systems. We argue that an explanation solution such as the one we endorse is required if we are to realize the full potential of hybrid, distributed, intelligent Web agents that users can trust and use.

On the Use of Web Services in Content Adaptation

The tremendous growth of the Internet has introduced a number of interoperability problems for distributed multimedia applications. These problems are related to the heterogeneity of client devices, network connectivity, content formats, and user’s preferences. The challenge is even bigger for multimedia content providers who are faced with the dilemma of finding the combination of different variants of a content to create, store, and send to their subscribers that maximize their satisfaction and hence entice them to come back. In this chapter, the authors will present a framework for trans-coding multimedia streams using an orchestration of Webservices. The framework takes into consideration the profile of communicating devices, network connectivity, exchanged content formats, context description, users’ preferences, and available adaptation services to find a chain of adaptation services that should be applied to the content to make it more satisfactory to clients. The framework was implemented as a core component for an architecture that supports personal and service mobility.

Search Engine-Based Web Information Extraction

In this chapter we discuss approaches to find, extract, and structure information from natural language texts on the Web. Such structured information can be expressed and shared using the standard Semantic Web languages and hence be machine interpreted. In this chapter we focus on two tasks in Web information extraction. The first part focuses on mining facts from the Web, while in the second part, we present an approach to collect community-based meta-data. A search engine is used to retrieve potentially relevant texts. From these texts, instances and relations are extracted. The proposed approaches are illustrated using various case-studies, showing that we can reliably extract information from the Web using simple techniques.

Modeling Best Practices in Web-Based Academic Development

This chapter makes a case for the importance of preparing e-teachers by requiring them to have an experience as an e-learner. The chapter begins with a review of the challenges and criticisms of e-learning. Some of the literature indicates that e-learners have been dissatisfied with their learning experiences. Some academics have concerns about the rigour of courses offered through e-learning. The literature of academic development and e-learning is used to link theory with practice. The chapter provides examples of best practice in the preparation of academic staff for e-teaching. Two case studies of lived examples of e-teaching preparation are provided from a North American perspective. Future research directions are outlined, with research questions to be explored regarding the link between the preparation of eteachers through e-learning and the quality of the e-learning experience for students.

Toward Mobile Web 2.0-Based Business Methods

Mobile service providers (MoSPs) emerge, driven by the ubiquitous availability of mobile devices and wireless communication infrastructures. MoSPs’ customers satisfaction and consequently their revenues, largely depend on the quality of service (QoS) provided by wireless network providers (WNPs) available at a particular location-time to support a mobile service delivery. This chapter presents a novel method for the MoSP’s QoS-assurance business process. The method incorporates a location- and time-based QoS-predictions’ service, facilitating the WNP’s selection. The authors explore different business cases for the service deployment. Particularly, they introduce and analyze business viability of QoSIS.net, an enterprise that can provide the QoS-predictions service to MoSPs, Mobile Network Operators (as MoSPs), or directly to their customers (i.e. in B2B/B2C settings). QoSIS.net provides its service based on collaborative-sharing of QoS-information by its users. The authors argue that this service can improve the MoSP’s QoS-assurance process and consequently may increase its revenues, while creating revenues for QoSIS.net.

Querying Web Accessibility Knowledge from Web Graphs

Web Accessibility is a hot topic today. Striving for social inclusion has resulted in the requirement of providing accessible content to all users. However, since each user is unique, and the Web evolves in a decentralized way, little or none is known about the shape of the Web’s accessibility on its own at a large scale, as well as from the point-of-view of each user. In this chapter the authors present the Web Accessibility Knowledge Framework as the foundation for specifying the relevant information about the accessibility of a Web page. This framework leverages Semantic Web technologies, side by side with audience modeling and accessibility metrics, as a way to study the Web as an entity with unique accessibility properties dependent from each user’s point of view. Through this framework, the authors envision a set of queries that can help harnessing and inferring this kind of knowledge from Web graphs.

Identifying Users Stereotypes for Dynamic Web Pages Customization

Adaptive Hypermedia is an effective approach to automatic personalization that overcomes the difficulties and deficiencies of traditional Web systems in delivering the appropriate content to users. One important issue regarding Adaptive Hypermedia systems is the construction and maintenance of the user profile. Another important concern is the use of Semantic Web resources to describe Web applications and to implement adaptation mechanisms. Web Usage Mining, in this context, allows the generation of Websites access patterns. This chapter describes the possibilities of integration of these usage patterns with semantic knowledge obtained from domain ontologies. Thus, it is possible to identify users’ stereotypes for dynamic Web pages customization. This integration of semantic knowledge can provide personalization systems with better adaptation strategies.

Exploiting Collaborative Tagging Systems to Unveil the User-Experience of Web Contents

The User Experience (UX) is a crucial factor for designing and enhancing the user satisfaction when interacting with a computational tool or with a system. Thus, measuring the UX can be very effective when designing or updating a Web site. Currently, there are many Web sites that rely on collaborative tagging: such systems allow users to add labels (tags) for categorizing contents. In this chapter the authors present a set of techniques for detecting the user experience through Collaborative Tagging Systems and we present an example on how to apply the approach for a Web site evaluation. This chapter highlights the potential use of collaborative tagging systems for measuring users’ satisfaction and discusses the future implications of this approach as compared to traditional evaluation tools, such as questionnaires, or interviews.

Swift Trust in Web Vendors

With the growth of product search engines such as pricegrabber.com, Web vendors have many more casual visitors. This research examines how Web vendors may foster “swift trust” as a means to convert casual visitors to paying customers. We examine whether perceptions of Web sites’ appearance features (normality, social presence and third-party links) and functionality features (security, privacy, effort expectancy and performance expectancy) positively relate to swift trust in a Web vendor. Using a quasi-experimental research design, we empirically test the proposed relationships. Based on an analysis of 224 respondents, we found appearance and functionality features explained 61% of the variance in swift trust. The article concludes with a discussion of findings and implications.