Collaborative filtering techniques have been successfully employed in recommender systems in order to help users deal with information overload by making high quality personalize...
Paul-Alexandru Chirita, Wolfgang Nejdl, Cristian Z...
In this paper we propose a recommender system that helps users to navigate though the Web by providing dynamically generated links to pages that have not yet been visited and are ...
Inexpensive data collection and storage technologies and a global thirst for information have led to data repositories so large that users may become disoriented and unable to loc...
Recommender systems are used by an increasing number of e-commerce websites to help the customers to find suitable products from a large database. One of the most popular techniqu...
Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thiem...
Recommender Systems are used in various domains to generate personalized information based on personal user data. The ability to preserve the privacy of all participants is an ess...
Abstract. Data Mining, or Knowledge Discovery as it is also known, is becoming increasingly useful in a wide variety of applications. In the following paper, we look at its use in ...
Abstract. Recommender systems have traditionally recommended items to individual users, but there has recently been a proliferation of recommenders that address their recommendatio...
This paper provides a comprehensive review of explanations in recommender systems. We highlight seven possible advantages of an explanation facility, and describe how existing mea...
Emotional context is becoming a promising paradigm to develop more intuitive and sensitive recommender systems. Ambient Recommender Systems, arise from the analysis of new trends ...
Recommender Systems (RS) so far have been applied to many fields of e-commerce in order to assist users in finding the products that best meet their preferences. However, while th...