Evaluating Recommender Systems: Survey and Framework

Evaluating Recommender Systems

Preface It was January 2007 when Dolf Trieschnigg, my supervisor for the course Information Retrieval , first told me about the availability of graduation projects at TNO Information and Communication Technology. This was a bull's eye since I just started to orientate myself on a subject to investigate. I was also looking for a company where I could perform my research since I wanted to get fam...

A Novel Multidimensional Framework for Evaluating Recommender Systems

The popularity of recommender systems has led to a large variety of their application. This, however, makes their evaluation a challenging problem, because different and often contrasting criteria are established, such as accuracy, robustness, and scalability. In related research, usually only condensed numeric scores such as RMSE or AUC or F-measure are used for evaluation of an algorithm on a...

Literature Survey: Recommender Systems

Recommender systems are intelligent systems which make suggestions about user items. Recommender system has become an important part of any entertainment or marketing website. As the recommender system has become so important it is a hot topic for any researcher. First paper on Recommender System was published in year 1998 since then more than 300 papers have been published in many of different...

Recommender systems survey

Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things. This article provides an overview of recommender systems as well as collaborative filteri...

Evaluating Preference-Based Feedback in Recommender Systems