2021/06/25 by Russell-Rose, Tony, Gooch, Philip, Kruschwitz, Udo · 1 citation
#FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Information Retrieval (cs.IR)
paper · doi:10.48550/arxiv.2106.13528
Knowledge workers (such as healthcare information professionals, patent agents and recruitment professionals) undertake work tasks where search forms a core part of their duties. In these instances, the search task is often complex and time-consuming and requires specialist expert knowledge to formulate accurate search strategies. Interactive features such as query expansion can play a key role in supporting these tasks. However, generating query suggestions within a professional search context requires that consideration be given to the specialist, structured nature of the search strategies they employ. In this paper, we investigate a variety of query expansion methods applied to a collection of Boolean search strategies used in a variety of real-world professional search tasks. The results demonstrate the utility of context-free distributional language models and the value of using linguistic cues such as ngram order to optimise the balance between precision and recall.