DEVELOPMENT OF A MODIFIED WINNOWING METHOD FOR AGGREGATING BIBLIOGRAPHIC INFORMATION DATA FROM CITATION SYSTEMS UNDER THE CONDITIONS OF INCOMPLETE INFORMATION
DOI:
https://doi.org/10.14529/ctcr200413Keywords:
citation system, scientometric methods, aggregation of bibliographic information, modification of the Winnowing method, Levenshtein method, shingle methodAbstract
Currently, transition to the electronic presentation of bibliographic information about scientific works has caused an increased interest in scientometric research. At the same time, the existing scientometric methods are criticized by scientists, since the incomplete bibliographic base and tools for its assessment do not allow the most accurate assessment of the contribution of scientific work. The problem of the quality of scientometric assessments, as a rule, is based on the study of the data of a certain citation system, which does not include complete information about all publications of the authors contained in other citation systems. Aim. This study is aimed at developing an adaptive approach for the formation of aggregated data of bibliographic information of a scientific organization in conditions of incomplete information from the citation systems of the RSCI, “Google Academy” and Scopus. Methods. The definition of the aggregated list of publications for the analysis of scientometric indicators was carried out by the Winnowing method, the Levenshtein algorithm,the shingle method and the Jaro–Winkler method. In the framework of the experimental study, the effectiveness of the application of the considered methods for aggregating information from citation systems was assessed based on the analysis of accuracy, completeness and F-measure. Results. Experiments on test data from the list of publications by authors of the Orenburg State University from the citation systems RSCI, Google Academy and Scopus showed that the Winnowing method formed the most accurate lists of publications by the F-measure criterion. To improve the performance of this algorithm, a two-stage optimization of the aggregation process was carried out, which made it possible to improve the running time of the algorithm when generating a list of bibliographic descriptions. Conclusion. The proposed approach for the formation of aggregated data of bibliographic information of a scientific organization in conditions of incomplete information from the citation systems of the Russian Science Citation Index, Google Academy and Scopus allows increasing productivity in the formation of a list of authors' publications and shows good efficiency in determining the scientometric characteristics of authors.
References
Yang, K. Citation Analysis: A Comparison of Google Scholar, Scopus, and Web of Science /
K. Yang, L.I. Meho // Proceedings of the American Society for Information Science and Tech-nology. – 2006. – Vol. 43, no. 1. – P. 1–15.
Collection statistics for fast duplicate document detection / A. Chowdhury, O. Frieder, D. Gros¬sman, C. Mccabe // ACM Trans. Inform. Syst. – 2002. – Vol. 20, no. 2. – P. 171–191.
Kotsemir, M.N. Publication Activity of Russian Researches in Leading International Scientific Journals / M.N. Kotsemir // Acta naturae. – 2012. – Vol. 4, no. 2 (13). – P. 15–35.
Мазов, Н.А. Программы для наукометрических и библиометрических исследований: краткий обзор и сравнительный анализ / Н.А. Мазов, В.Н. Гуреев // Труды 15-й Всерос-сийской научной конференции «Электронные библиотеки: перспективные методы и технологии, электронные коллекции». – 2013. – С. 23–28.
Косинов, Д.И. Использование статистической информации при выявлении схожих документов / Д.И. Косиянов // Сборник «Интернет-математика». – 2007. – С. 84–90.
Baneyx, A. «Publish or Perish» as citation metrics used to analyze scientific output in the humanities: international case studies in economics, geography, social sciences, philosophy, and history / A. Baneyx // Archivum Immunologiae et Therapiae Experimentalis. – 2008. – Vol. 56, no. 6. – P. 363–371.
Болдырев, П.А. Обзор программных средств в области анализа публикационной активности учёных / П.А. Болдырев, И.Б. Крылов // XXIII студенческая международная заоч-ная научно-практическая конференция «Молодёжный научный форум: технические и математические науки». – 2015. – http://nauchforum.ru/ru/node/6914 (дата обращения: 01.10.2020).
Квелидзе-Кузнецова, Н.Н. Библиометрические показатели как оценочный критерий деятельности преподавателя университета / Н.Н. Квелидзе-Кузнецова, С.А. Морозова // Universum: Вестник Герценовского университета. – 2009. – № 4. – С. 38–45.
Москалева, О.В. Потери публикаций России: почему и как избежать? / О.В. Москалева // 4-я Международная научно-практическая конференция «Научное издание международного уровня – 2015: современные тенденции в мировой практике редактирования, издания и оценки научных публикаций». – 2015. – С. 87–91.
Полянин, А.Д. Об индексе Хирша и других наукометрических показателях / А.Д. Полянин // Научное сообщество. – 2013. – № 8–9. – С. 20–22.
Штовба, С.Д. Обзор наукометрических показателей для оценки публикационной активности учёного / С.Д. Штовба, Е.В. Штовба // Управление большими системами. Специальный выпуск 44: «Наукометрия и экспертиза в управлении наукой» . – 2013. – С. 262–278.
Холодов, А.С. Об индексах цитирования научных работ / А.С. Холодов // Вестник Рос-сийской академии наук. – 2015. – Т. 85, № 4. – С. 310–320.
Garcia-Perez, M.A. The Hirsch h index in a nonmainstream area: methodology of the behavioral sciences in Spain / M.A. Garcia-Perez // The Spanish Journal of Psychology. – 2009. – Vol. 12, no. 2. – P. 833–849.
Egghe, L. Mathematical theory of the h- and g-index in case of fractional counting of author-ship / L. Egghe // Journal of the American Society for Information Science and Technology. – 2008. – Vol. 59, no. 10. – P. 1608–1616.
Krylov, I.B. Several characteristics of existing automated systems according to survey of rus-sian scientists publishing activity / I.B. Krylov, P.A. Boldyrev // Theoretical & Applied Science. – 2015. – no. 5 (25). – P. 6–9.
