Search (24 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. 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
  5. Tho, Q.T.; Hui, S.C.; Fong, A.C.M.: ¬A citation-based document retrieval system for finding research expertise (2007) 0.02 
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    Abstract
    Current citation-based document retrieval systems generally offer only limited search facilities, such as author search. In order to facilitate more advanced search functions, we have developed a significantly improved system that employs two novel techniques: Context-based Cluster Analysis (CCA) and Context-based Ontology Generation frAmework (COGA). CCA aims to extract relevant information from clusters originally obtained from disparate clustering methods by building relationships between them. The built relationships are then represented as formal context using the Formal Concept Analysis (FCA) technique. COGA aims to generate ontology from clusters relationship built by CCA. By combining these two techniques, we are able to perform ontology learning from a citation database using clustering results. We have implemented the improved system and have demonstrated its use for finding research domain expertise. We have also conducted performance evaluation on the system and the results are encouraging.
  6. 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
  7. Gabel, J.: Improving information retrieval of subjects through citation-analysis : a study (2006) 0.01 
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    Source
    Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
  8. Jiang, X.; Liu, J.: Extracting the evolutionary backbone of scientific domains : the semantic main path network analysis approach based on citation context analysis (2023) 0.01 
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    Abstract
    Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT-based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top-K main paths extracted from various time slices of semantic citation network. In addition, a three-way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics-agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas.
  9. 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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    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.
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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."
  17. 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
  18. H-Index auch im Web of Science (2008) 0.01 
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    Date
    6. 4.2008 19:04:22
  19. 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
  20. 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

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