Search (31 results, page 2 of 2)

  • × language_ss:"e"
  • × theme_ss:"Citation indexing"
  1. Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.01 
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    Date
    22. 8.2014 16:52:04
  2. Brooks, T.A.: How good are the best papers of JASIS? (2000) 0.01 
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    Content
    Top by numbers of citations: (1) Saracevic, T. et al.: A study of information seeking and retrieving I-III (1988); (2) Bates, M.: Information search tactics (1979); (3) Cooper, W.S.: On selecting a measure of retrieval effectiveness (1973); (4) Marcus, R.S.: A experimental comparison of the effectiveness of computers and humans as search intermediaries (1983); (4) Fidel, R.: Online searching styles (1984)
  3. Chen, C.; Cribbin, T.; Macredie, R.; Morar, S.: Visualizing and tracking the growth of competing paradigms : two case studies (2002) 0.01 
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  4. Frandsen, T.F.; Rousseau, R.: Article impact calculated over arbitrary periods (2005) 0.01 
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  5. Boyack, K.W.; Small, H.; Klavans, R.: Improving the accuracy of co-citation clustering using full text (2013) 0.01 
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  6. Hu, X.; Rousseau, R.: Do citation chimeras exist? : The case of under-cited influential articles suffering delayed recognition (2019) 0.01 
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  7. Rousseau, R.; Zuccala, A.: ¬A classification of author co-citations : definitions and search strategies (2004) 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. Klitzing, N.; Hoekstra, R.; Strijbos, J.-W,: Literature practices : processes leading up to a citation (2019) 0.01 
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  10. Safder, I.; Ali, M.; Aljohani, N.R.; Nawaz, R.; Hassan, S.-U.: Neural machine translation for in-text citation classification (2023) 0.01 
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  11. Wouters, P.; Vries, R. de: Formally citing the Web (2004) 0.01 
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