Seed‐based information retrieval in networks of research publications: Evaluation of direct citations, bibliographic coupling, co‐citations, and PubMed‐related article score
IF 2.8 2区 管理学Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
{"title":"Seed‐based information retrieval in networks of research publications: Evaluation of direct citations, bibliographic coupling, co‐citations, and PubMed‐related article score","authors":"Peter Sjögårde, Per Ahlgren","doi":"10.1002/asi.24951","DOIUrl":null,"url":null,"abstract":"In this contribution, we deal with seed‐based information retrieval in networks of research publications. Using systematic reviews as a baseline, and publication data from the NIH Open Citation Collection, we compare the performance of the three citation‐based approaches direct citation, co‐citation, and bibliographic coupling with respect to recall and precision measures. In addition, we include the PubMed‐related article score as well as combined approaches in the comparison. We also provide a fairly comprehensive review of earlier research in which citation relations have been used for information retrieval purposes. The results show an advantage for co‐citation over bibliographic coupling and direct citation. However, combining the three approaches outperforms the exclusive use of co‐citation in the study. The results further indicate, in line with previous research, that combining citation‐based approaches with textual approaches enhances the performance of seed‐based information retrieval. The results from the study may guide approaches combining citation‐based and textual approaches in their choice of citation similarity measures. We suggest that future research use more structured approaches to evaluate methods for seed‐based retrieval of publications, including comparative approaches as well as the elaboration of common data sets and baselines for evaluation.","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"37 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Association for Information Science and Technology","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1002/asi.24951","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In this contribution, we deal with seed‐based information retrieval in networks of research publications. Using systematic reviews as a baseline, and publication data from the NIH Open Citation Collection, we compare the performance of the three citation‐based approaches direct citation, co‐citation, and bibliographic coupling with respect to recall and precision measures. In addition, we include the PubMed‐related article score as well as combined approaches in the comparison. We also provide a fairly comprehensive review of earlier research in which citation relations have been used for information retrieval purposes. The results show an advantage for co‐citation over bibliographic coupling and direct citation. However, combining the three approaches outperforms the exclusive use of co‐citation in the study. The results further indicate, in line with previous research, that combining citation‐based approaches with textual approaches enhances the performance of seed‐based information retrieval. The results from the study may guide approaches combining citation‐based and textual approaches in their choice of citation similarity measures. We suggest that future research use more structured approaches to evaluate methods for seed‐based retrieval of publications, including comparative approaches as well as the elaboration of common data sets and baselines for evaluation.
期刊介绍:
The Journal of the Association for Information Science and Technology (JASIST) is a leading international forum for peer-reviewed research in information science. For more than half a century, JASIST has provided intellectual leadership by publishing original research that focuses on the production, discovery, recording, storage, representation, retrieval, presentation, manipulation, dissemination, use, and evaluation of information and on the tools and techniques associated with these processes.
The Journal welcomes rigorous work of an empirical, experimental, ethnographic, conceptual, historical, socio-technical, policy-analytic, or critical-theoretical nature. JASIST also commissions in-depth review articles (“Advances in Information Science”) and reviews of print and other media.