A visual approach to search strategy formulation

Knowledge workers (such as healthcare information professionals, patent agents and legal researchers) need to undertake complex search tasks to identify relevant documents and insights within large domain-specific repositories and collections. The traditional solution is to use line-by-line query builders offered by proprietary database vendors. However, these offer limited support for error checking or query optimization, and their output can often be compromised by errors and inefficiencies. In this talk, we present a new approach to query formulation in which concepts are expressed as objects on a two-dimensional canvas, and relationships are articulated by direct manipulation. Automated search term suggestions are provided using a combination of knowledge-based and statistical NLP techniques. This has the potential to eliminate many sources of inefficiency, make the query semantics more transparent, and offer a universal framework for search strategy formulation.