Search (38 results, page 1 of 2)

  • × theme_ss:"Citation indexing"
  1. Nicolaisen, J.: Citation analysis (2007) 0.03 
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    Date
    13. 7.2008 19:53:22
  2. Døsen, K.: One more reference on self-reference (1992) 0.03 
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    Date
    7. 2.2005 14:10:22
  3. 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
  4. Rajan, T.N.; Guha, B.; Sayanarayana, R.: Associate relationship of concepts as seen through citations and citation index (1982) 0.02 
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    Source
    Universal classification II: subject analysis and ordering systems. Proc. of the 4th Int. Study Conf. on Classification research, Augsburg, 28.6.-2.7.1982. Ed.: I. Dahlberg
  5. Malanga, G.: Classifying and screening journal literature with citation data (1982) 0.02 
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    Source
    Universal classification I: subject analysis and ordering systems. Proc. of the 4th Int. Study Conf. on Classification Research, Augsburg, 28.6.-2.7.1982. Ed.: I. Dahlberg
  6. Peritz, B.C.: ¬A classification of citation roles for the social sciences and related fields (1983) 0.02 
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  7. Kwok, K.L.: ¬The use of titles and cited titles as document representations for automatic classification (1975) 0.02 
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  8. 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
  9. 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.
  10. Safder, I.; Ali, M.; Aljohani, N.R.; Nawaz, R.; Hassan, S.-U.: Neural machine translation for in-text citation classification (2023) 0.02 
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    Abstract
    The quality of scientific publications can be measured by quantitative indices such as the h-index, Source Normalized Impact per Paper, or g-index. However, these measures lack to explain the function or reasons for citations and the context of citations from citing publication to cited publication. We argue that citation context may be considered while calculating the impact of research work. However, mining citation context from unstructured full-text publications is a challenging task. In this paper, we compiled a data set comprising 9,518 citations context. We developed a deep learning-based architecture for citation context classification. Unlike feature-based state-of-the-art models, our proposed focal-loss and class-weight-aware BiLSTM model with pretrained GloVe embedding vectors use citation context as input to outperform them in multiclass citation context classification tasks. Our model improves on the baseline state-of-the-art by achieving an F1 score of 0.80 with an accuracy of 0.81 for citation context classification. Moreover, we delve into the effects of using different word embeddings on the performance of the classification model and draw a comparison between fastText, GloVe, and spaCy pretrained word embeddings.
  11. 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
  12. Pichappan, P.: Levels of citation relation between papers (1996) 0.01 
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    Abstract
    Proposes a typology for measuring the levels of citation relations netween papers. Introduces a new family of citation based classification schemes and outlines the typology that can be seen as being analogous to Ranganathan's APUPA pattern in subject mapping
  13. 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
  14. 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.
  15. 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.
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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

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