Database offers on-the-fly results.
Declan Butler
A new Internet database lets users generate on-the-fly citation statistics of published research papers for free. The tool also calculates papers' impact factors using a new algorithm similar to PageRank, the algorithm Google uses to rank web pages. The open-access database is collaborating with Elsevier, the giant Amsterdam-based science publisher, and its underlying data come from Scopus, a subscription abstracts database created by Elsevier in 2004.
The SCImago Journal & Country Rank database was launched in December by SCImago, a data-mining and visualization group at the universities of Granada, Extremadura, Carlos III and Alcalá de Henares, all in Spain. It ranks journals and countries using such citation metrics as the popular, if controversial, Hirsch Index. It also includes a new metric: the SCImago Journal Rank (SJR).
The familiar impact factor created by industry leader Thomson Scientific, based in Philadelphia, Pennsylvania, is calculated as the average number of citations by the papers that each journal contains. The SJR also analyses the citation links between journals in a series of iterative cycles, in the same way as the Google PageRank algorithm. This means not all citations are considered equal; those coming from journals with higher SJRs are given more weight. The main difference between SJR and Google's PageRank is that SJR uses a citation window of three years. See Table 1
C. Aggarwal, и P. Yu. Proceedings of the 2000 ACM SIGMOD International Conference on
Management of Data, May 16-18, 2000, Dallas, Texas, USA, стр. 70-81. ACM, (2000)
E. Agirre, E. Alfonseca, K. Hall, J. Kravalova, M. Pasca, и A. Soroa. Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, стр. 19--27. Stroudsburg, PA, USA, Association for Computational Linguistics, (2009)
R. Agrawal, J. Gehrke, D. Gunopulos, и P. Raghavan. Proceedings of the ACM SIGMOD Int'l Conference on Management of
Data, Seattle, Washington, стр. 94--105. ACM Press, (июня 1998)
R. Agrawal, T. Imielinski, и A. Swami. SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data, стр. 207--216. New York, NY, USA, ACM Press, (1993)
R. Agrawal, и R. Srikant. VLDB '94: Proceedings of the 20th International Conference on Very Large Data Bases, стр. 487--499. San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., (1994)
Z. Al Bawab, G. Mills, и J. Crespo. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, стр. 397--405. New York, NY, USA, ACM, (2012)
D. Andrzejewski, и X. Zhu. Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing, стр. 43--48. Stroudsburg, PA, USA, Association for Computational Linguistics, (2009)
G. Angeli, и C. Manning. Proceedings of the Seventeenth Conference on Computational Natural Language Learning, стр. 133--142. Sofia, Bulgaria, Association for Computational Linguistics, (августа 2013)
A. Arasu, и H. Garcia-Molina. Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diego, California, USA, June 9-12, 2003, стр. 337-348. ACM, (2003)
L. Arras, A. Osman, K. Müller, и W. Samek. Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, стр. 113--126. Florence, Italy, Association for Computational Linguistics, (августа 2019)
M. Artetxe, G. Labaka, I. Lopez-Gazpio, и E. Agirre. Proceedings of the 22nd Conference on Computational Natural Language Learning, стр. 282--291. Association for Computational Linguistics, (2018)
M. Atzmueller, D. Benz, A. Hotho, и G. Stumme (Ред.) Technical report (KIS), 2010-10 Department of Electrical Engineering/Computer Science, Kassel University, (2010)