Reducing Click Distance through Social Adaptive Interfacing∗

Interface options offered to users for extracting content from information repositories such as YouTube are 1-dimensional. Users are presented with ubiquitous flat lists of content in menus and result lists, from which they must identify interesting content. Previous work has concentrated on the areas of user profiling and content filtering in order to retrieve and present relevant content to users as they explore repositories. In this paper we consider how traditional information access interfaces might be enhanced to facilitate exploratory search by providing users with a variety of different social cues with which to judge the relevance of different types of information assets. In this work we report on a multi-dimensional interface for repository collections which brings forward information pertaining to previous navigation trails from various starting points on the users current location. This allows users to gain a more informed view of the options available to them and also allows users to skip steps in the trails presented thus reducing the effort required to satisfy their goals.