Collaborative querying using the Query Graph Visualizer.

Abstract

Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. We address this issue from the perspective of collaborative querying, an approach that helps users formulate queries by harnessing the collective knowledge of other searchers. We describe the design and implementation of the Query Graph Visualizer (QGV), a collaborative querying system which harvests and clusters previously issued queries to form query networks that represent related information needs. The queries in the network are explored in the QGV, helping users locate other queries that might meet their current information needs. A preliminary evaluation of the QGV is also described and results suggest the usefulness and

usability of the system.