During the last ten years numerous research instruments emerged for evaluating the service quality of Web-based information systems. B2C recommender systems are information systems that support users in selecting information, products, or services improving their decision making process. Unfortunately, the majority of these instruments do not acknowledge the full range of recommendation functio...

Recommender systems have become essential in many web sites, especially in the e-commerce area; however, they are not extended enough in some domains. In this work, a recommender system for TV series is presented due to the increasing interest for this kind of products. The system implements a methodology that deals with the most important problems of recommender systems.

Recommender systems help customers to choose right product or service from large number of alternatives available on Internet. In recent time, trust becomes an important issue in designing effective recommender systems. In this paper we have studied the role of trust and distrust in designing recommender systems. General Terms E-Commerce, Information Retrieval, Web Mining.

The paper aims to present research results on using Web 2.0 tools for learning personalisation. In the work, personalised Web 2.0 tools selection method is presented. This method takes into account student’s learning preferences for content and communication modes tailored to the learning activities with a view to help the learner to quickly and accurately find the right educational tools, and ...

This paper proposes a methodology to optimise the future accuracy of a collaborative recommender application in a citizen Web portal. There are four stages namely, user modelling, benchmarking of clustering algorithms, prediction analysis and recommendation. The first stage is to develop analytical models of common characteristics of Web-user data. These artificial data sets are then used to ev...

A web recommender system assists a user to manage the vast amount of search results suggested by a search engine when surfing the Web with the help of recommender system agents. In this case the recommender system will reduce the effort a user has to spend in searching and navigating to important web pages or web documents and simultaneously increases the user ability to find more relevant docu...

In view of information overflow on the web, the use of recommender systems seems to be an appropriate means by which to organize information that targets preferences. The purpose of this article is to present a novel model explaining the satisfaction with recommender websites integrating emerging influential factors such as trust, exploratory browsing, and personal factors. Three recommender sy...

In this demo we show a recommender system, called SUGGEST, that dynamically generates links to pages that have not yet been visited by a user and might be of his potential interest. Usually other recommender systems exploit a kind of two-phase architecture composed by an off-line component that analyzes Web server access logs and generates information used by a successive online component that ...

Association rules are a widely used technique to generate recommendations in commercial and research recommender systems. Since more and more Web sites, especially of retailers, offer automatic recommender services using Web usage mining, evaluation of recommender algorithms becomes increasingly important. In this paper we first present a framework for the evaluation of different aspects of rec...