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Egghe, L.; Rousseau, R.: Topological aspects of information retrieval (1998)
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- Abstract
- Let (DS, DQ, sim) be a retrieval system consisting of a document space DS, a query space QS, and a function sim, expressing the similarity between a document and a query. Following D.M. Everett and S.C. Cater (1992), we introduce topologies on the document space. These topologies are generated by the similarity function sim and the query space QS. 3 topologies will be studied: the retrieval topology, the similarity topology and the (pseudo-)metric one. It is shown that the retrieval topology is the coarsest of the three, while the (pseudo-)metric is the strongest. These 3 topologies are generally different, reflecting distinct topological aspects of information retrieval. We present necessary and sufficient conditions for these topological aspects to be equal
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Egghe, L.; Liang, L.; Rousseau, R.: ¬A relation between h-index and impact factor in the power-law model (2009)
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- Abstract
- Using a power-law model, the two best-known topics in citation analysis, namely the impact factor and the Hirsch index, are unified into one relation (not a function). The validity of our model is, at least in a qualitative way, confirmed by real data.
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Egghe, L.; Guns, R.; Rousseau, R.; Leuven, K.U.: Erratum (2012)
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- Date
- 14. 2.2012 12:53:22
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Kretschmer, H.; Rousseau, R.: Author inflation leads to a breakdown of Lotka's law : in and out of context (2001)
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- Abstract
- Fractional counting of authors of multi-authored papers has been shown to lead to a breakdown of Lotka's Law despite its robust character under most circumstances. Kretschmer and Rousseau use the normal count method of full credit for each author on two five-year bibliographies from each of 13 Dutch physics institutes where high co-authorship is a common occurrence. Kolmogorov-Smirnov tests were preformed to see if the Lotka distribution fit the data. All bibliographies up to 40 authors fit acceptably; no bibliography with a paper with over 100 authors fits the distribution. The underlying traditional "success breeds success" mechanism assumes new items on a one by one basis, but Egghe's generalized model would still account for the process. It seems unlikely that Lotka's Law will hold in a high co-authorship environment.
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Egghe, L.; Guns, R.; Rousseau, R.: Thoughts on uncitedness : Nobel laureates and Fields medalists as case studies (2011)
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- Abstract
- Contrary to what one might expect, Nobel laureates and Fields medalists have a rather large fraction (10% or more) of uncited publications. This is the case for (in total) 75 examined researchers from the fields of mathematics (Fields medalists), physics, chemistry, and physiology or medicine (Nobel laureates). We study several indicators for these researchers, including the h-index, total number of publications, average number of citations per publication, the number (and fraction) of uncited publications, and their interrelations. The most remarkable result is a positive correlation between the h-index and the number of uncited articles. We also present a Lotkaian model, which partially explains the empirically found regularities.
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Shi, D.; Rousseau, R.; Yang, L.; Li, J.: ¬A journal's impact factor is influenced by changes in publication delays of citing journals (2017)
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- Abstract
- In this article we describe another problem with journal impact factors by showing that one journal's impact factor is dependent on other journals' publication delays. The proposed theoretical model predicts a monotonically decreasing function of the impact factor as a function of publication delay, on condition that the citation curve of the journal is monotone increasing during the publication window used in the calculation of the journal impact factor; otherwise, this function has a reversed U shape. Our findings based on simulations are verified by examining three journals in the information sciences: the Journal of Informetrics, Scientometrics, and the Journal of the Association for Information Science and Technology.
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Yang, B.; Rousseau, R.; Wang, X.; Huang, S.: How important is scientific software in bioinformatics research? : a comparative study between international and Chinese research communities (2018)
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- Abstract
- Software programs are among the most important tools in data-driven research. The popularity of well-known packages and corresponding large numbers of citations received bear testimony of the contribution of scientific software to academic research. Yet software is not generally recognized as an academic outcome. In this study, a usage-based model is proposed with varied indicators including citations, mentions, and downloads to measure the importance of scientific software. We performed an investigation on a sample of international bioinformatics research articles, and on a sample from the Chinese community. Our analysis shows that scientists in the field of bioinformatics rely heavily on scientific software: the major differences between the international community and the Chinese example being how scientific packages are mentioned in publications and the time gap between the introduction of a package and its use. Biologists publishing in international journals tend to apply the latest tools earlier; Chinese scientists publishing in Chinese tend to follow later. Further, journals with higher impact factors tend to publish articles applying the latest tools earlier.
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Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996)
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- Source
- Journal of information science. 22(1996) no.3, S.165-170
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Asonuma, A.; Fang, Y.; Rousseau, R.: Reflections on the age distribution of Japanese scientists (2006)
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- Date
- 22. 7.2006 15:26:24
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Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003)
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- Date
- 9. 7.2006 10:22:35
