Academic information retrieval using citation clusters: in-depth evaluation based on systematic reviews
Scientometrics, vol. 128, pp. 2895–2921
Abstract
Abstract The field of science mapping has shown the power of citation-based clusters for literature analysis, yet this technique has barely been used for information retrieval tasks. This work evaluates the performance of citation-based clusters for information retrieval tasks. We simulated a search process with a tree hierarchy of clusters and a cluster selection algorithm. We evaluated the task of finding the relevant documents for 25 systematic reviews. Our evaluation considered several trade-offs between recall and precision for the cluster selection. We also replicated the Boolean queries self-reported by the systematic reviews to serve as a reference. We found that citation-based clusters’ search performance is highly variable and unpredictable, that the clusters work best for users that prefer recall over precision at a ratio between 2 and 8, and that the clusters are able to complement query-based search by finding additional relevant documents.
Authors 4
-
Juan Pablo Bascur corresponding Aachen Centre for Science and Technology Studies Leiden Institute for Advanced Computer Science
Affiliation as printed
Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands
Leiden Institute for Advanced Computer Science, Leiden University, Leiden, The Netherlands
-
Affiliation as printed
Leiden Institute for Advanced Computer Science, Leiden University, Leiden, The Netherlands
-
Affiliation as printed
Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands
-
Affiliation as printed
Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands
Cited by 52 stored of 52
No patents citing this paper on Lens.org (checked 2026-10-11).