Retrieving haystacks: a data driven information needs model for faceted search.
Cleverley, Paul Hugh
Burnett, Simon M.
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CLEVERLEY, P. H. and BURNETT, S., 2015. Retrieving haystacks: a data driven information needs model for faceted search. Journal of Information Science, 41 (1), pp. 97-113.
The research aim was to develop an understanding of information need characteristics for word co-occurrence-based search result filters (facets). No prior research has been identified into what enterprise searchers may find useful for exploratory search and why. Various word co-occurrence techniques were applied to results from sample queries performed on industry membership content. The results were used in an international survey of 54 practising petroleum engineers from 32 organizations. Subject familiarity, job role, personality and query specificity are possible causes for survey response variation. An information needs model is presented: Broad, Rich, Intriguing, Descriptive, General, Expert and Situational (BRIDGES). This may help professionals to more effectively meet their information needs and stimulate new needs, improving a system’s ability to facilitate serendipity. This research has implications for faceted search in enterprise search and digital library deployments.