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  • × language_ss:"e"
  • × theme_ss:"Citation indexing"
  1. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.03
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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
  2. Hjerppe, R.: ¬An outline of bibliometrics and citation analysis (1980) 0.02
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    Type
    r
  3. Milman, B.L.: Individual co-citation clusters as nuclei of complete and dynamic informetric models of scientific and technological areas (1994) 0.02
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    Abstract
    Describes the construction of improved informetric models of individual scientific and technological areas on the basis of individual co citation clusters. The developed methodology of replenishment of research front with accidently absent papers describes the model more completely. Proposes the simple method of cluster 'dynamization' for the study of evolution of research area. The transition under consideration from co citation clusters to lexical maps of papers and patents enables the monitoring of the relationshuip between R and D in a given technological area. Provides the example from modern chemical engineering of Pressure-Swing Adsorption
  4. Nicolaisen, J.: Citation analysis (2007) 0.02
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    Date
    13. 7.2008 19:53:22
  5. Døsen, K.: One more reference on self-reference (1992) 0.02
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    Date
    7. 2.2005 14:10:22
  6. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.01
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    Date
    22. 7.2006 15:22:28
  7. Page, L.; Brin, S.; Motwani, R.; Winograd, T.: ¬The PageRank citation ranking : Bringing order to the Web (1999) 0.01
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  8. Lai, K.-K.; Wu, S.-J.: Using the patent co-citation approach to establish a new patent classification system (2005) 0.01
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    Abstract
    The paper proposes a new approach to create a patent classification system to replace the IPC or UPC system for conducting patent analysis and management. The new approach is based on co-citation analysis of bibliometrics. The traditional approach for management of patents, which is based on either the IPC or UPC, is too general to meet the needs of specific industries. In addition, some patents are placed in incorrect categories, making it difficult for enterprises to carry out R&D planning, technology positioning, patent strategy-making and technology forecasting. Therefore, it is essential to develop a patent classification system that is adaptive to the characteristics of a specific industry. The analysis of this approach is divided into three phases. Phase I selects appropriate databases to conduct patent searches according to the subject and objective of this study and then select basic patents. Phase II uses the co-cited frequency of the basic patent pairs to assess their similarity. Phase III uses factor analysis to establish a classification system and assess the efficiency of the proposed approach. The main contribution of this approach is to develop a patent classification system based on patent similarities to assist patent manager in understanding the basic patents for a specific industry, the relationships among categories of technologies and the evolution of a technology category.
  9. Rajan, T.N.; Guha, B.; Sayanarayana, R.: Associate relationship of concepts as seen through citations and citation index (1982) 0.01
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  10. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.01
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    Date
    22. 3.2009 19:22:35
  11. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01
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    Date
    17.12.2013 11:02:22
  12. Rousseau, R.: Timelines in citation research (2006) 0.01
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  13. Castro, R. de; Grossmann, J.W.: Famous trails to Paul Erdös (1999) 0.01
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  14. Garfield, E.: Recollections of Irving H. Sher 1924-1996 : Polymath/information scientist extraordinaire (2001) 0.01
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    Date
    16.12.2001 14:01:22
  15. Van der Veer Martens, B.; Goodrum, G.: ¬The diffusion of theories : a functional approach (2006) 0.01
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    Date
    22. 7.2006 15:20:01
  16. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.01
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    Date
    17.11.2020 12:22:59
  17. Campanario, J.M.: Have referees rejected some of the most-cited articles of all times? (1996) 0.01
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    Abstract
    In this article a quantitative study is reported on the resistance that scientists may encounter when they do innovative work or when they attempt to publish articles that later become highly cited. A set of 205 commentaries by authors of some of the most-cited papers of all times have been examined in order to identify those articles whose authors encountered difficulty in getting his or her work published. There are 22 commentaries (10,7%) in which authors mention some difficulty or resistance in doing or publishing the research reported in the article. Three of the articles which had problems in being published are the most cited from their respective journals. According the authors' commentaries, although sometimes referees' negative evaluations can help improve the articles, in other instances referees and editors wrongly rejected the highly cited articles
  18. Snyder, H.; Bonzi, S.: Patterns of self-citation across disciplines : 1980-1989 (1998) 0.01
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    Date
    22. 5.1999 19:33:24
  19. Chan, H.C.; Kim, H.-W.; Tan, W.C.: Information systems citation patterns from International Conference on Information Systems articles (2006) 0.01
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    Date
    3. 1.2007 17:22:03
  20. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.01
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    Date
    26.12.2007 19:22:05

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