Reasoning on the Web is gaining in importance because of emerging Web applications such as contextadaptive Web systems (e.g. eLearning, recommender, personalised (multi-)media, and mobile information systems), Web service retrieval and composition, and Semantic Web applications of all kinds. A central issue is combining automated reasoning methods with Web languages, especially with Web query, ...

Information overload is no longer news; the explosive growth of the Internet has made this issue increasingly serious for Web users. Recommender systems aim at directing users through this information space, toward the resources that best meet their needs and interests. In this chapter we introduce our novel machine learning perspective toward the web recommendation problem, based on reinforcem...

The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introdu...

Collaborative tagging systems are harnessing the power of online communities, making the task of knowledge contribution more attractive to a broader audience of Web users. In particular, social bookmarking systems have shifted the organization of bookmarks from an individual activity performed on a personal desktop to a collective endeavor over the Web. In such a context, suggestive tagging has...

BACKGROUND What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior t...

Personalization tailors a user’s interaction with the Web information space based on information gathered about them. Declarative user information such as manually entered profiles continue to raise privacy concerns and are neither scalable nor flexible in the face of very active dynamic Web sites and changing user trends and interests. One way to deal with this problem is through a completely ...

In the recent years, the Web has undergone a tremendous growth regarding both content and users. This has lead to an information overload problem in which people are finding it increasingly difficult to locate the right information at the right time. Recommender systems have been developed to address this problem, by guiding users through the big ocean of information. Until now, recommender sys...

Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basically, recommender systems experience many issues which reflects dwindled effectiveness. Integrating powerful data management techniques to recommende...

Nowadays, the application of data mining techniques in e-learning and web based adaptive educational system is increasing exponentially. The discovered useful information can be used directly by the teacher or the author of the course to improve the instructional/learning performance. This can be an arduous task and therefore educational recommender systems are used in order to help the teacher...