Bibliometric-enhanced information retrieval: preface
Author:
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Computer Science Applications,General Social Sciences
Link
http://link.springer.com/article/10.1007/s11192-018-2861-0/fulltext.html
Reference14 articles.
1. Abdulhayoglu, M. A., & Thijs, B. (2018). Use of locality sensitive hashing (LSH) algorithm to match Web of Science and Scopus. Scientometrics. https://doi.org/10.1007/s11192-017-2569-6 .
2. Cagliero, L., Garza, P., Kavoosifar, M. R., & Baralis, E. (2018). Discovering cross-topic collaborations among researchers by exploiting weighted association rules. Scientometrics. https://doi.org/10.1007/s11192-018-2737-3 .
3. Giles, C. L. (2013). Scholarly big data. In: CIKM’13: Proceedings of the 22nd ACM international conference on conference on information and knowledge management (p. 1). ACM, New York, NY. https://doi.org/10.1145/2505515.2527109 .
4. Heffernan, K., & Teufel, S. (2018). Identifying problems and solutions in scientific text. Scientometrics. https://doi.org/10.1007/s11192-018-2718-6 .
5. Kacem, A., & Mayr, P. (2018). Analysis of search stratagem utilisation. Scientometrics. https://doi.org/10.1007/s11192-018-2821-8 .
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