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Out now: Roy, Carevic & Mayr: Retrievability in an integrated retrieval system: an extended study.


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Roy, D., Carevic, Z. & Mayr, P. Retrievability in an integrated retrieval system: an extended study. Int J Digit Libr (2023).

https://doi.org/10.1007/s00799-023-00363-4

Retrievability measures the influence a retrieval system has on the access to information in a given collection of items. This measure can help in making an evaluation of the search system based on which insights can be drawn. In this paper, the authors investigate the retrievability in an integrated search system consisting of items from various categories, particularly focussing on datasets, publications and variables in a real-life digital library.

The traditional metrics, that is, the Lorenz curve and Gini coefficient, are employed to visualise the diversity in retrievability scores of the three retrievable document types (specifically datasets, publications, and variables). Their results show a significant popularity bias with certain items being retrieved more often than others. Particularly, it has been shown that certain datasets are more likely to be retrieved than other datasets in the same category. In contrast, the retrievability scores of items from the variable or publication category are more evenly distributed. The authors have observed that the distribution of document retrievability is more diverse for datasets as compared to publications and variables.