The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed. The book is the first
Tutorial Abstract The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become fabvbamiliar with state-of-the-art recommendation me
Tutorial Abstract The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become fabvbamiliar with state-of-the-art recommendation me
Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. The suggestions provided are aimed at supporting their users in various decision-making processes, such as what items to buy, what music to
The aim of a web-based recommender system is to pro- vide highly accurate and up-to-date recommendations to its users; in practice, it will hope to retain its users over time. However, this raises unique challenges. To achieve complex goals such as
推荐系统，基于上下文信息的推荐系统 The importance of contextual information has been recognized by re- searchers and practitioners in many disciplines, including e-commerce personal- ization, information retrieval, ubiquitous and mobile computing, data mining, mar-
This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability
