SmartSearch: automated recommendations using librarian expertise and the National Center for Biotechnology Information's Entrez Programming Utilities

Abstract

Librarians are in the recommendation business. Our customers rely on us to recommend what they should read, which database is preferable over another, or which textbook might answer a background question. As digital gate counts increase and outpace traditional face-to-face interactions [1], the need to integrate librarian recommendations into digital systems grows. SmartSearch represents an automated approach to offering digital expert guidance to customers. The Lane Medical Library & Knowledge Management Center provides information access and knowledge management services for the Stanford University School of Medicine, Stanford Hospital, and the Lucile Packard Children's Hospital. Lane's mission is to get the right knowledge, to the right person, at the right time, in the right context to support translational research, innovative education, and advances in patient care. This is largely accomplished via the LaneConnex web interface [2], a library search platform that performs a metasearch across hundreds of licensed and open access knowledge resources. Like many academic health libraries, Lane's clinical collection consists of thousands of electronic journals and textbooks. This wealth of knowledge is daunting to users who are often overwhelmed by the sheer quantity of information. Lane's usage statistics show that clinical users consistently overlook expensive clinical resources (e.g., specialty textbooks from AccessMedicine, MDConsult, and Ovid) that librarians have selected for their high value and clinical relevance. SmartSearch addresses this issue. The goal of the SmartSearch project is to recommend a small number of infrequently consulted, high-value, clinically relevant resources in the context of a standard LaneConnex search. SmartSearch is a resource promotion tool that leverages librarian expertise with the Entrez Programming Utilities (E-Utilities) [3] from the National Center for Biotechnology Information (NCBI) to mimic the information-seeking behavior of a typical reference librarian. System design, development, and an evaluation of its effectiveness will be described.