Abstract
Recommender systems (RS) support users who need personalized access to large collections of data. From a technical perspective, RSs have their origins in different fields such as information filtering and data mining, and they are built using a broad array of statistical methods and algorithms. E-commerce and consumer decision support applications have been the traditional application domains of these types of systems. However, the ever-increasing plethora of information supply due to cheap storage, the web revolution and user-generated content applications, fuels the need for user-centric and context-aware information access and presentation in many more database application domains. The aim of this workshop is therefore to provide a forum for discussion and presentation of the latest results on the intersection of database and recommender systems research.