Search (79 results, page 1 of 4)

  • × 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) 0.05 
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    Abstract
    Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however, limited, as it assumes all citations are of similar value and weights each equally. Content-based citation analysis (CCA) addresses a citation's value by interpreting each one based on its context at both the syntactic and semantic levels. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full-text resources have opened this area of research to vast possibilities, which enable deeper citation analysis, more accurate citation prediction, and increased knowledge discovery.
    Date
    22. 8.2014 16:52:04
  2. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.05 
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    Abstract
    This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.
    Date
    17.12.2013 11:02:22
  3. Chan, H.C.; Kim, H.-W.; Tan, W.C.: Information systems citation patterns from International Conference on Information Systems articles (2006) 0.03 
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    Abstract
    Research patterns could enhance understanding of the Information Systems (IS) field. Citation analysis is the methodology commonly used to determine such research patterns. In this study, the citation methodology is applied to one of the top-ranked Information Systems conferences - International Conference on Information Systems (ICIS). Information is extracted from papers in the proceedings of ICIS 2000 to 2002. A total of 145 base articles and 4,226 citations are used. Research patterns are obtained using total citations, citations per journal or conference, and overlapping citations. We then provide the citation ranking of journals and conferences. We also examine the difference between the citation ranking in this study and the ranking of IS journals and IS conferences in other studies. Based on the comparison, we confirm that IS research is a multidisciplinary research area. We also identify the most cited papers and authors in the IS research area, and the organizations most active in producing papers in the top-rated IS conference. We discuss the findings and implications of the study.
    Date
    3. 1.2007 17:22:03
  4. Ma, N.; Guan, J.; Zhao, Y.: Bringing PageRank to the citation analysis (2008) 0.03 
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    Abstract
    The paper attempts to provide an alternative method for measuring the importance of scientific papers based on the Google's PageRank. The method is a meaningful extension of the common integer counting of citations and is then experimented for bringing PageRank to the citation analysis in a large citation network. It offers a more integrated picture of the publications' influence in a specific field. We firstly calculate the PageRanks of scientific papers. The distributional characteristics and comparison with the traditionally used number of citations are then analyzed in detail. Furthermore, the PageRank is implemented in the evaluation of research influence for several countries in the field of Biochemistry and Molecular Biology during the time period of 2000-2005. Finally, some advantages of bringing PageRank to the citation analysis are concluded.
    Date
    31. 7.2008 14:22:05
  5. Mendez, A.: Some considerations on the retrieval of literature based on citations (1978) 0.03 
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  6. Cronin, B.: Bibliometrics and beyond : some thoughts on web-based citation analysis (2001) 0.02 
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  7. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.02 
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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
  8. Bradshaw, S.; Hammond, K.: Using citations in facilitate precise indexing and automatic index creation in collections of research papers (2001) 0.02 
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    Source
    Knowledge-based systems. 14(2001) nos.1/2, S.20-35
  9. He, Y.; Hui, S.C.: PubSearch : a Web citation-based retrieval system (2001) 0.02 
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    Abstract
    Many scientific publications are now available on the World Wide Web for researchers to share research findings. However, they tend to be poorly organised, making the search of relevant publications difficult and time-consuming. Most existing search engines are ineffective in searching these publications, as they do not index Web publications that normally appear in PDF (portable document format) or PostScript formats. Proposes a Web citation-based retrieval system, known as PubSearch, for the retrieval of Web publications. PubSearch indexes Web publications based on citation indices and stores them into a Web Citation Database. The Web Citation Database is then mined to support publication retrieval. Apart from supporting the traditional cited reference search, PubSearch also provides document clustering search and author clustering search. Document clustering groups related publications into clusters, while author clustering categorizes authors into different research areas based on author co-citation analysis.
  10. 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.
  11. Nicolaisen, J.: Citation analysis (2007) 0.02 
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    Date
    13. 7.2008 19:53:22
  12. Døsen, K.: One more reference on self-reference (1992) 0.02 
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    Date
    7. 2.2005 14:10:22
  13. Sidiropoulos, A.; Manolopoulos, Y.: ¬A new perspective to automatically rank scientific conferences using digital libraries (2005) 0.02 
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    Abstract
    Citation analysis is performed in order to evaluate authors and scientific collections, such as journals and conference proceedings. Currently, two major systems exist that perform citation analysis: Science Citation Index (SCI) by the Institute for Scientific Information (ISI) and CiteSeer by the NEC Research Institute. The SCI, mostly a manual system up until recently, is based on the notion of the ISI Impact Factor, which has been used extensively for citation analysis purposes. On the other hand the CiteSeer system is an automatically built digital library using agents technology, also based on the notion of ISI Impact Factor. In this paper, we investigate new alternative notions besides the ISI impact factor, in order to provide a novel approach aiming at ranking scientific collections. Furthermore, we present a web-based system that has been built by extracting data from the Databases and Logic Programming (DBLP) website of the University of Trier. Our system, by using the new citation metrics, emerges as a useful tool for ranking scientific collections. In this respect, some first remarks are presented, e.g. on ranking conferences related to databases.
  14. Boyack, K.W.; Small, H.; Klavans, R.: Improving the accuracy of co-citation clustering using full text (2013) 0.02 
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    Abstract
    Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.
  15. Pichappan, P.: Levels of citation relation between papers (1996) 0.02 
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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
  16. 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
  17. 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.
  18. 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.
  19. MacCain, K.W.: Descriptor and citation retrieval in the medical behavioral sciences literature : retrieval overlaps and novelty distribution (1989) 0.01 
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    Abstract
    Search results for nine topics in the medical behavioral sciences are reanalyzed to compare the overall perfor-mance of descriptor and citation search strategies in identifying relevant and novel documents. Overlap per- centages between an aggregate "descriptor-based" database (MEDLINE, EXERPTA MEDICA, PSYCINFO) and an aggregate "citation-based" database (SCISEARCH, SOCIAL SCISEARCH) ranged from 1% to 26%, with a median overlap of 8% relevant retrievals found using both search strategies. For seven topics in which both descriptor and citation strategies produced reasonably substantial retrievals, two patterns of search performance and novelty distribution were observed: (1) where descriptor and citation retrieval showed little overlap, novelty retrieval percentages differed by 17-23% between the two strategies; (2) topics with a relatively high percentage retrieval overlap shoed little difference (1-4%) in descriptor and citation novelty retrieval percentages. These results reflect the varying partial congruence of two literature networks and represent two different types of subject relevance
  20. Shaw, W.M.: Subject and citation indexing : pt.1: the clustering structure of composite representations in the cystic fibrosis document collection (1991) 0.01 
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    Abstract
    The presence of clustering structure in the CF document collection (cystic fibrosis) is evaluated as a function of the exhaustivity of 5 composite representations. The composite representations are constructed from 2 subject descriptions, based on MeSH and subheadings, and 2 citation indexes, based on the complete set of references an and a comprehensive set of citations to each document. Experiment results reveal observable evidence of clustering structure diminishes as the exhaustivity of each representation is decreased. The representation composed of references and citations shows less evidence of clustering structure at the exhaustive level but more uniform evidence of clustering structure over a wide range of exhaustivity levels than composite representations that include subject descriptions. The structures imposed on the CF document collection by all composite representations satisfy the necessary condition for a meaningful clustering outcome

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