Interactive query expansion for professional search applications
I'm delighted to report that our paper 'Interactive query expansion for professional search applications' has just been published in the journal Business Information Review. It's been a long time in the making, primarily as the work was completed over a prolonged period of time involving many iterations, not all of which were successful (in the product development sense). But it does represent a concise summary of our work in investigating knowledge-based and distributional (word embedding) approaches to the generation of interactive query suggestions for professional search (which, I should point out, poses a qualitatively different and greater challenge than query suggestions for traditional keyword/web search). In fact, this paper represents an abridged version of the full results, since for reasons of space we were obliged to omit certain techniques that were less successful. For full details of those, please refer to our pre-print on arXiv.
Anyway, feedback so far has been very informative. Keep it coming in! New release coming soon, so happy to accommodate thoughts & suggestions. Abstract appended below.
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 to optimise the balance between precision and recall.
Read full article.