{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T09:47:56Z","timestamp":1770371276752,"version":"3.49.0"},"reference-count":16,"publisher":"Walter de Gruyter GmbH","issue":"4","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To address the \u201canomalies\u201d that occur when scientific breakthroughs emerge, this study focuses on identifying early signs and nascent stages of breakthrough innovations from the perspective of outliers, aiming to achieve early identification of scientific breakthroughs in papers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>This study utilizes semantic technology to extract research entities from the titles and abstracts of papers to represent each paper\u2019s research content. Outlier detection methods are then employed to measure and analyze the anomalies in breakthrough papers during their early stages. The development and evolution process are traced using literature time tags. Finally, a case study is conducted using the key publications of the 2021 Nobel Prize laureates in Physiology or Medicine.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>Through manual analysis of all identified outlier papers, the effectiveness of the proposed method for early identifying potential scientific breakthroughs is verified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Research limitations<\/jats:title>\n                    <jats:p>The study\u2019s applicability has only been empirically tested in the biomedical field. More data from various fields are needed to validate the robustness and generalizability of the method.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Practical implications<\/jats:title>\n                    <jats:p>This study provides a valuable supplement to current methods for early identification of scientific breakthroughs, effectively supporting technological intelligence decision-making and services.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/Value<\/jats:title>\n                    <jats:p>The study introduces a novel approach to early identification of scientific breakthroughs by leveraging outlier analysis of research entities, offering a more sensitive, precise, and fine-grained alternative method compared to traditional citation-based evaluations, which enhances the ability to identify nascent breakthrough innovations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2478\/jdis-2024-0027","type":"journal-article","created":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T04:45:09Z","timestamp":1725425109000},"page":"90-109","source":"Crossref","is-referenced-by-count":2,"title":["Early identification of scientific breakthroughs through outlier analysis based on research entities"],"prefix":"10.2478","volume":"9","author":[{"given":"Yang","family":"Zhao","sequence":"first","affiliation":[{"name":"National Science Library, Chinese Academy of Sciences , Beijing , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengting","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Science Library, Chinese Academy of Sciences , Beijing , China"},{"name":"Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences , Beijing , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoli","family":"Chen","sequence":"additional","affiliation":[{"name":"National Science Library, Chinese Academy of Sciences , Beijing , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhixiong","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Science Library, Chinese Academy of Sciences , Beijing , China"},{"name":"Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences , Beijing , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"key":"2026020518342464704_j_jdis-2024-0027_ref_001","doi-asserted-by":"crossref","unstructured":"Bansal, R., Gaur, N., & Singh, S. N. (2016). Outlier detection: applications and techniques in data mining. 2016 6th International conference-cloud system and big data engineering (Confluence), Noida, India, 373\u2013377, doi: 10.1109\/CONFLUENCE.2016.7508146","DOI":"10.1109\/CONFLUENCE.2016.7508146"},{"key":"2026020518342464704_j_jdis-2024-0027_ref_002","doi-asserted-by":"crossref","unstructured":"Chen, X., & Han, T. (2021). Early Detection of Emerging Technologies using Temporal Features. Predicting the Dynamics of Research Impact, 253\u2013269.","DOI":"10.1007\/978-3-030-86668-6_12"},{"key":"2026020518342464704_j_jdis-2024-0027_ref_003","doi-asserted-by":"crossref","unstructured":"Gu, Y., Tinn, R., Cheng, H., Lucas, M., Usuyama, N., Liu, X., Naumann, T., Gao, J., & Poon, H. (2021). Domain-specific language model pretraining for biomedical natural language processing. 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Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084.","DOI":"10.18653\/v1\/D19-1410"},{"key":"2026020518342464704_j_jdis-2024-0027_ref_010","doi-asserted-by":"crossref","unstructured":"Savov, P., Jatowt, A., & Nielek, R. (2020). Identifying breakthrough scientific papers. Information Processing & Management, 57(2), 102168.","DOI":"10.1016\/j.ipm.2019.102168"},{"key":"2026020518342464704_j_jdis-2024-0027_ref_011","doi-asserted-by":"crossref","unstructured":"Schneider, J. W., & Costas, R. (2017). Identifying potential \u201cbreakthrough\u201d publications using refined citation analyses: Three related explorative approaches. Journal of the Association for Information Science and Technology, 68(3), 709\u2013723.","DOI":"10.1002\/asi.23695"},{"key":"2026020518342464704_j_jdis-2024-0027_ref_012","doi-asserted-by":"crossref","unstructured":"Small, H., Tseng, H., & Patek, M. (2017). 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