Use of locality sensitive hashing (LSH) algorithm to match Web of Science and Scopus

Author:

Abdulhayoglu Mehmet Ali,Thijs Bart

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Science Applications,General Social Sciences

Reference17 articles.

1. Abdulhayoglu, M. A., & Thijs, B. (2017). Use of locality sensitive hashing (LSH) algorithm to match Web of Science and SCOPUS. In Proceedings of the fifth workshop on bibliometric-enhanced information retrieval (BIR) co-located with the 39th European conference on information retrieval (ECIR), Aberdeen, UK (pp. 30–40).

2. Abdulhayoglu, M. A., Thijs, B., & Jeuris, W. (2016). Using character n-grams to match a list of publications to references in bibliographic databases. Scientometrics, 109(3), 1525–1546.

3. Bosman, J., Mourik, I. V., Rasch, M., Sieverts, E., & Verhoeff, H. (2006). Scopus reviewed and compared: The coverage and functionality of the citation database Scopus, including comparisons with Web of Science and Google Scholar. Utrecht University Library.

4. Chang, C.-C., & Lin, C.-J. (2011). LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2,27:1–27:27. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm .

5. Charikar, M. S. (2002). Similarity estimation techniques from rounding algorithms. In Proceedings of the thiry-fourth annual ACM symposium on Theory of computing (pp. 380–388). ACM.

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