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Computer Science > Digital Libraries

arXiv:2207.03299 (cs)
[Submitted on 7 Jul 2022 (v1), last revised 5 Oct 2023 (this version, v2)]

Title:Academic information retrieval using citation clusters: In-depth evaluation based on systematic reviews

Authors:Juan Pablo Bascur, Suzan Verberne, Nees Jan van Eck, Ludo Waltman
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Abstract:The field of scientometrics 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 using these clusters 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, and we also replicated the Boolean queries self-reported by the systematic review to serve as a reference. We found that citation-based clusters search performance is highly variable and unpredictable, that it works best for users that prefer recall over precision at a ratio between 2 and 8, and that when used along with query-based search they complement each other, including finding new relevant documents.
Comments: Final version
Subjects: Digital Libraries (cs.DL)
Cite as: arXiv:2207.03299 [cs.DL]
  (or arXiv:2207.03299v2 [cs.DL] for this version)
  https://doi.org/10.48550/arXiv.2207.03299

Submission history

From: Juan Bascur [view email]
[v1] Thu, 7 Jul 2022 13:50:27 UTC (1,072 KB)
[v2] Thu, 5 Oct 2023 15:42:11 UTC (1,079 KB)
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