Search (20 results, page 1 of 1)

  • × theme_ss:"Citation indexing"
  • × year_i:[2000 TO 2010}
  1. Nicolaisen, J.: Citation analysis (2007) 0.03 
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    Date
    13. 7.2008 19:53:22
  2. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.02 
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    Date
    22. 7.2006 15:22:28
  3. Garfield, E.; Stock, W.G.: Citation Consciousness : Interview with Eugene Garfiels, chairman emeritus of ISI; Philadelphia (2002) 0.02 
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    Source
    Password. 2002, H.6, S.22-25
  4. Lai, K.-K.; Wu, S.-J.: Using the patent co-citation approach to establish a new patent classification system (2005) 0.02 
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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.
  5. 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
  6. Rousseau, R.; Zuccala, A.: ¬A classification of author co-citations : definitions and search strategies (2004) 0.01 
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    Abstract
    The term author co-citation is defined and classified according to four distinct forms: the pure first-author co-citation, the pure author co-citation, the general author co-citation, and the special co-authorlco-citation. Each form can be used to obtain one count in an author co-citation study, based an a binary counting rule, which either recognizes the co-citedness of two authors in a given reference list (1) or does not (0). Most studies using author co-citations have relied solely an first-author cocitation counts as evidence of an author's oeuvre or body of work contributed to a research field. In this article, we argue that an author's contribution to a selected field of study should not be limited, but should be based an his/her complete list of publications, regardless of author ranking. We discuss the implications associated with using each co-citation form and show where simple first-author co-citations fit within our classification scheme. Examples are given to substantiate each author co-citation form defined in our classification, including a set of sample Dialog(TM) searches using references extracted from the SciSearch database.
  7. Leydesdorff, L.: Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports (2004) 0.01 
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    Abstract
    The aggregated journal-journal citation matrix derived from Journal Citation Reports 2001 can be decomposed into a unique subject classification using the graph-analytical algorithm of bi-connected components. This technique was recently incorporated in software tools for social network analysis. The matrix can be assessed in terms of its decomposability using articulation points which indicate overlap between the components. The articulation points of this set did not exhibit a next-order network of "general science" journals. However, the clusters differ in size and in terms of the internal density of their relations. A full classification of the journals is provided in the Appendix. The clusters can also be extracted and mapped for the visualization.
  8. 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
  9. 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
  10. wst: Cut-and-paste-Wissenschaft (2003) 0.01 
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    Content
    "Mikhail Simkin und Vwani Roychowdhury von der University of Califomia, Los Angeles, haben eine in der wissenschaftlichen Gemeinschaft verbreitete Unsitte erstmals quantitativ erfasst. Die Wissenschaftler analysierten die Verbreitung von Druckfehlern in den Literaturlisten wissenschaftlicher Arbeiten (www.arxiv.org/abs/cond-mat/0212043). 78 Prozent aller zitierten Aufsätze - so schätzen die Forscher - haben die zitierenden Wissenschaftler demnach nicht gelesen, sondern nur per 'cut and paste' von einer Vorlage in ihre eigene Literaturliste übernommen. Das könne man beispielsweise abschätzen aus der Analyse fehlerhafter Seitenangaben in der Literaturliste eines 1973 veröffentlichten Aufsatzes über die Struktur zweidimensionaler Kristalle: Dieser Aufsatz ist rund 4300 mal zitiert worden. In 196 Fällen enthalten die Zitate jedoch Fehler in der Jahreszahl, dem Band der Zeitschrift oder der Seitenzahl, die als Indikatoren für cut and paste genommen werden können, denn man kann, obwohl es Milliarden Möglichkeiten gibt, nur 45 verschiedene Arten von Druckfehlern unterscheiden. In erster Näherung ergibt sich eine Obergrenze für die Zahl der `echten Leser' daher aus der Zahl der unterscheidbaren Druckfehler (45) geteilt durch die Gesamtzahl der Publikationen mit Druckfehler (196), das macht etwa 22 Prozent."
  11. 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
  12. H-Index auch im Web of Science (2008) 0.01 
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    Date
    6. 4.2008 19:04:22
  13. 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
  14. Ma, N.; Guan, J.; Zhao, Y.: Bringing PageRank to the citation analysis (2008) 0.01 
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    Date
    31. 7.2008 14:22:05
  15. Thelwall, M.; Harries, G.: ¬The connection between the research of a university and counts of links to its Web pages : an investigation based upon a classification of the relationships of pages to the research of the host university (2003) 0.01 
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  16. Hayer, L.: Lazarsfeld zitiert : eine bibliometrische Analyse (2008) 0.01 
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    Date
    22. 6.2008 12:54:12
  17. Leydesdorff, L.: Can scientific journals be classified in terms of aggregated journal-journal citation relations using the Journal Citation Reports? (2006) 0.01 
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    Abstract
    The aggregated citation relations among journals included in the Science Citation Index provide us with a huge matrix, which can be analyzed in various ways. By using principal component analysis or factor analysis, the factor scores can be employed as indicators of the position of the cited journals in the citing dimensions of the database. Unrotated factor scores are exact, and the extraction of principal components can be made stepwise because the principal components are independent. Rotation may be needed for the designation, but in the rotated solution a model is assumed. This assumption can be legitimated on pragmatic or theoretical grounds. Because the resulting outcomes remain sensitive to the assumptions in the model, an unambiguous classification is no longer possible in this case. However, the factor-analytic solutions allow us to test classifications against the structures contained in the database; in this article the process will be demonstrated for the delineation of a set of biochemistry journals.
  18. Pudovkin, A.I.; Garfield, E.: Algorithmic procedure for finding semantically related journals (2002) 0.01 
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    Abstract
    Journal Citation Reports provides a classification of journals most heavily cited by a given journal and which most heavily cite that journal, but size variation is not taken into account. Pudovkin and Garfield suggest a procedure for meeting this difficulty. The relatedness of journal i to journal j is determined by the number of citations from journal i to journal j in a given year normalized by the product of the papers published in the j journal in that year times the number of references cited in the i journal in that year. A multiplier of ten to the sixth is suggested to bring the values into an easily perceptible range. While citations received depend upon the overall cumulative number of papers published by a journal, the current year is utilized since that data is available in JCR. Citations to current year papers would be quite low in most fields and thus not included. To produce the final index, the maximum of the A citing B value, and the B citing A value is chosen and used to indicate the closeness of the journals. The procedure is illustrated for the journal Genetics.
  19. Wildner, B.: Web of Science - Scopus : Auf der Suche nach Zitierungen (2006) 0.01 
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    Date
    4. 6.2006 17:22:15
  20. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.01 
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    Date
    9. 7.2006 10:22:35

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