Design and Development of a Query Graph Visualization System

Collaborative querying is a technique that harnesses the collective search experiences of users to assist in query formulation. We present the Query Graph Visualizer (QGV), a visual collaborative querying system that recommends related queries to a user’s submitted query through a network visualization scheme. Users are able to explore the query network and select queries for execution on an information retrieval (IR) system. The QGV is not meant to be a replacement for IR systems but as a value-added module to help users search more effectively. Consequently, the QGV is not an IR system but works in tandem with existing IR systems. The design of the QGV is discussed, focusing on its architecture, the interaction between the QGV’s main components and the implementation of the user interface. An evaluation of the QGV was also conducted to assess the performance of the system against to a conventional search engine. Results indicate that the evaluators who used the QGV completed their tasks much faster compared to those using a search engine alone. A usability evaluation also showed that the system complied with standard user interface heuristics.

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