Personalized or recommender systems are a particular type of information filtering applications. User profiles, representing the information needs and preferences of users, can be inferred from log or clickthrough data, or the ratings that users provide on information items, through their interactions with a system. Such user profiles have been used, for example in iGoogle, to provide personali...

With the increasing adoption of Web services, designing novel approaches for recommending relevant Web services has become of paramount importance especially to support many practical applications such as Web services composition. In this paper, a survey aiming at encompassing the state-of-the-art interactive Web services composition recommendation approaches is presented. Both Web services com...

Prediction of user future movements and intentions based on the users’ clickstream data is a main challenging problem in Web based recommendation systems. Web usage mining based on the users’ clickstream data has become the subject of exhaustive research, as its potential for web based personalized services, predicting user near future intentions, adaptive Web sites and customer profiling is re...

Reactivity, the ability to detect and react to events, is an essential functionality in many information systems. In particular, Web systems such as online marketplaces, adaptive (e.g., recommender) systems, and Web services, react to events such as Web page updates or data posted to a server. This article investigates issues of relevance in designing high-level programming languages dedicated ...

A recommender system is an information filtering technology which can be used to predict preference ratings of items (products, services, movies, etc) and/or to output a ranking of items that are likely to be of interest to the user. Context-aware recommender systems (CARS) learn and predict the tastes and preferences of users by incorporating available contextual information in the recommendat...

In recent years, several methods for generating and presenting personalized information have been developed. They are aimed at taming the information overload caused by the vast range of continuously growing content available on the World Wide Web. Examples include adaptive hypertext, which adapts the user interface to the users interests and needs (e.g., in mobile portals), and recommender sys...

Web programmers are often faced with several challenges in the development process of modern, rich internet applications. Technologies for the different tiers of the application have to be selected: a serverside language, a combination of JavaScript, HTML and CSS for the client, and a database technology. Meeting the expectations of contemporary web applications requires even more effort from t...

Web recommender systems anticipate the information needs of on-line users and provide them with recommendations to facilitate and personalize their navigation. A variety of approaches have been attempted and proposed. Among them, using Web access logs to generate users’ navigational profiles for recommendation is a popular one, given its non-intrusiveness. However, using only one information ch...

The Web is one of the most important information media and it is influencing in the development of other media, as for example, newspapers, journals, books, libraries, etc. Moreover, in recent days people want to communicate and collaborate. So, libraries must develop services for connecting people together in information environments. Then, the library staff needs automatic techniques to facil...

The explosive growth in the amount of information available in the WWW and the emergence of e-commerce in recent years has demanded new ways to deliver personalized content. Recommender systems [51] have emerged in this context as a solution based on collective intelligence to either predict whether a particular user will like a particular item or identify the collection of items that will be o...