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  • × author_ss:"Rousseau, R."
  1. Egghe, L.; Rousseau, R.: Introduction to informetrics : quantitative methods in library, documentation and information science (1990) 0.01 
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    COMPASS
    Information science / Statistical mathematics
    Date
    29. 2.2008 19:02:46
    LCSH
    Information science / Statistical methods
    Subject
    Information science / Statistical mathematics
    Information science / Statistical methods
  2. Egghe, L.; Guns, R.; Rousseau, R.; Leuven, K.U.: Erratum (2012) 0.01 
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    Date
    14. 2.2012 12:53:22
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.2, S.429
  3. Rousseau, R.: Timelines in citation research (2006) 0.01 
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    Abstract
    The timeline used in ISI's Journal Citation Reports (JCR; Thomson ISI, formerly the Institute for Scientific Information, Philadelphia, PA) for half-life calculations, is not a timeline for (average) cited age. These two timelines are shifted over half a year.
    Date
    18. 8.2006 14:29:40
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.10, S.1404-1405
  4. Liu, Y.; Rousseau, R.: Citation analysis and the development of science : a case study using articles by some Nobel prize winners (2014) 0.01 
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    Date
    29. 1.2014 16:31:35
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.2, S.281-289
  5. Shi, D.; Rousseau, R.; Yang, L.; Li, J.: ¬A journal's impact factor is influenced by changes in publication delays of citing journals (2017) 0.01 
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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.
    Date
    16.11.2017 13:29:52
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.3, S.780-789
  6. Frandsen, T.F.; Rousseau, R.: Article impact calculated over arbitrary periods (2005) 0.01 
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    Date
    20. 3.2005 10:29:08
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.1, S.58-62
  7. Colebunders, R.; Kenyon, C.; Rousseau, R.: Increase in numbers and proportions of review articles in Tropical Medicine, Infectious Diseases, and oncology (2014) 0.01 
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    Date
    29. 1.2014 15:56:36
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.1, S.201-205
  8. Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996) 0.01 
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    Source
    Journal of information science. 22(1996) no.3, S.165-170
  9. Asonuma, A.; Fang, Y.; Rousseau, R.: Reflections on the age distribution of Japanese scientists (2006) 0.01 
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    Date
    22. 7.2006 15:26:24
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.342-346
  10. 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) 0.01 
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    Date
    29. 9.2018 12:36:19
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.9, S.1122-1133
  11. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.00 
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    Abstract
    Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
    Date
    9. 7.2006 10:22:35
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.6, S.549-568
  12. Rousseau, S.; Rousseau, R.: Metric-wiseness (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2389
  13. Egghe, L.; Rousseau, R.: ¬A theoretical study of recall and precision using a topological approach to information retrieval (1998) 0.00 
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    Abstract
    Topologies for information retrieval systems are generated by certain subsets, called retrievals. Shows how recall and precision can be expressed using only retrievals. Investigates different types of retrieval systems: both threshold systems and close match systems and both optimal and non optimal retrieval. Highlights the relation with the hypergeometric and some non-standard distributions
    Source
    Information processing and management. 34(1998) nos.2/3, S.191-218
  14. Rousseau, R.; Ye, F.Y.: ¬A proposal for a dynamic h-type index (2008) 0.00 
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    Abstract
    A time-dependent h-type indicator is proposed. This indicator depends on the size of the h-core, the number of citations received, and recent change in the value of the h-index. As such, it tries to combine in a dynamic way older information about the source (e.g., a scientist or research institute that is evaluated) with recent information.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.11, S.1853-1855
  15. Egghe, L.; Rousseau, R.: Topological aspects of information retrieval (1998) 0.00 
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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
    Source
    Journal of the American Society for Information Science. 49(1998) no.13, S.1144-1160
  16. Rousseau, R.: Bradford curves (1994) 0.00 
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    Source
    Information processing and management. 30(1994) no.2, S.267-277
  17. Rousseau, R.: Egghe's g-index is not a proper concentration measure (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.7, S.1518-1519
  18. Egghe, L.; Rousseau, R.: Duality in information retrieval and the hypegeometric distribution (1997) 0.00 
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    Abstract
    Asserts that duality is an important topic in informetrics, especially in connection with the classical informetric laws. Yet this concept is less studied in information retrieval. It deals with the unification or symmetry between queries and documents, search formulation versus indexing, and relevant versus retrieved documents. Elaborates these ideas and highlights the connection with the hypergeometric distribution
  19. Rousseau, R.: On Egghe's construction of Lorenz curves (2007) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.10, S.1551-1552
  20. Liu, Y.; Rousseau, R.: Towards a representation of diffusion and interaction of scientific ideas : the case of fiber optics communication (2012) 0.00 
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    Abstract
    The research question studied in this contribution is how to find an adequate representation to describe the diffusion of scientific ideas over time. We claim that citation data, at least of articles that act as concept symbols, can be considered to contain this information. As a case study we show how the founding article by Nobel Prize winner Kao illustrates the evolution of the field of fiber optics communication. We use a continuous description of discrete citation data in order to accentuate turning points and breakthroughs in the history of this field. Applying the principles explained in this contribution informetrics may reveal the trajectories along which science is developing.
    Source
    Information processing and management. 48(2012) no.4, S.791-801

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