Web augmentation techniques allow the adaptation of websites on client side using browser extensions or plug-ins designed to run dedicated user scripts. However, while number and variety of such scripts from publicly available repositories have grown remarkably in recent years, they usually neglect the user’s personal profile or individual preferences, and therefore fail to provide enhanced per...

Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. The motive of mining is to find users’ access models automatically and quickly from the vast Web log data, such as frequent access paths, frequent access page groups and user clustering. Through web usage mining, the server log, registration information and other rel...

—Nowadays, the application of data mining techniques in e-learning and web based adaptive educational systems 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 teach...

Knowledge-based recommender systems are Web-based applications that exploit deep domain knowledge for generating buying proposals that match the individual needs and requirements of an online user. As in many domains the detailed customer requirements have to be elicited in an interactive dialog before the recommendation can be made, the development and in particular also the maintenance of the...

We outline the history of recommender systems from their roots in information retrieval and filtering to their role in today’s Internet economy. Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. Research in recommender systems lies at the intersection of several areas of computer science...

In this paper we propose to use social tagging systems for Web page recommendation. Using social bookmarking systems allows the recommender to recommend web pages from various domains as opposed to web usage recommenders which are able to recommend pages in a very restricted domain. In this paper we use clustering and principle component analysis to construct the recommendations for each user a...

I want to propose a general framework for user-oriented and content-based recommender systems aimed at providing preferential multicriteria rating on Web Pages and automatic user’s profile generation and updating through logic programming techniques.

Number of people who use internet and websites for various purposes is increasing at an astonishing rate. More and more people rely on online sites for purchasing songs, apparels, books, rented movies etc. The competition between the online sites forced the web site owners to provide personalized services to their customers. So the recommender systems came into existence. Recommender systems ar...

Automatic and non-invasive web personalization seems to be a challenge for nowadays web sites. Many web mining techniques are used to achieve this goal. Since current web sites evolve constantly, web mining operations should be periodically repeated. A multi-agent architecture facilitates integration of different mining methods and permits the discovered knowledge to be verified and updated aut...