Russell-Rose, Tony; Gooch, Philip and Kruschwitz, Udo. 2021. Interactive query expansion for professional search applications. Business Information Review, 38(3), pp. 127-137. ISSN 0266-3821 [Article]

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Abstract or Description

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.

Item Type:	Article
Identification Number (DOI):	https://doi.org/10.1177/02663821211034079
Additional Information:	This research was supported by Innovate UK Open Competition R&D grant 102975, ‘Intelligent Search Assistance’. Test data is publicly available via Github. Evaluation code is hosted on BitBucket and can be made available on demand.
Keywords:	Information retrieval, machine learning, natural language processing, ontologies, professional search, query expansion
Departments, Centres and Research Units:	Computing
Dates:	Date Event September 2021 Published 23 July 2021 Published Online 29 June 2021 Accepted
Item ID:	30375
Date Deposited:	27 Jul 2021 14:10
Last Modified:	22 Nov 2021 11:06
Peer Reviewed:	Yes, this version has been peer-reviewed.
URI:	https://research.gold.ac.uk/id/eprint/30375

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