Recommender systems are software frameworks that employ a specific type of information filtering technique, aiming at recommending information items or social elements that are likely to be of interest to the user. Herein, we present the evaluation results of the recently prototyped Tourism Recommender System (TRS). We followed a formal evaluation process...

Personal learning environment (PLE) solutions aim at empowering learners to design (ICT and web-based) environments for their activities in different learning contexts and even for transitions between these contexts. Hereby, recommender systems which are highly successful in other application areas comprise one relevant technology for supporting learners in PLE-based activities. In this paper w...

A recommender system is a web-based application aiming for helping customers in the decision making and product selection process by providing a list of recommended items. Due to data scarcity, satisfactory recommendation results will be infeasible to generate. By joining recommender system databases, E-commerce websites can expand their datasets to provide more accurate recommendations. While ...

The use of personalized recommender systems to assist users in the selection of products is becoming more and more popular and wide-spread. The purpose of a recommender system is to provide the most suitable items from an knowledge base, according the user knowledge, tastes, interests, ... These items are generally proposed as ordered lists. In this article, we propose to combine works from ada...

Recently recommender systems started to gain ground in commercial Web-applications. For example, the online-bookseller amazon. com recommends his customers books similar to the ones they bought using the analysis of observed purchase behavior of consumers. In this article we describe a generic architecture for recommender services for information markets which has been implemented in the settin...

In this paper, we introduce a framework for modular generation of context-aware recommendations. The components of this framework include context sensors, recommender algorithms and utility modules (converters and filters), all realized as so-called services, which can flexibly be combined in terms of a recommender construction kit. Different areas of an application (e. g. a web portal) thus ca...

WHO estimates that the number of people with diabetes will grow 114% by 2030.It declares that, patients have to play a major role to control and therapy of diabetes by being provided with updated knowledge about the disease and different aspects of available treatments, diet therapy in particular. In this regard, diets recommender Systems would be helpful. They are techniques and tools which su...

the evaluation and selection of recommender systems is a difficult decision making process. this difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. as such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...