Search (77 results, page 1 of 4)

  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. Liu, D.-R.; Shih, M.-J.: Hybrid-patent classification based on patent-network analysis (2011) 0.06 
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    Abstract
    Effective patent management is essential for organizations to maintain their competitive advantage. The classification of patents is a critical part of patent management and industrial analysis. This study proposes a hybrid-patent-classification approach that combines a novel patent-network-based classification method with three conventional classification methods to analyze query patents and predict their classes. The novel patent network contains various types of nodes that represent different features extracted from patent documents. The nodes are connected based on the relationship metrics derived from the patent metadata. The proposed classification method predicts a query patent's class by analyzing all reachable nodes in the patent network and calculating their relevance to the query patent. It then classifies the query patent with a modified k-nearest neighbor classifier. To further improve the approach, we combine it with content-based, citation-based, and metadata-based classification methods to develop a hybrid-classification approach. We evaluate the performance of the hybrid approach on a test dataset of patent documents obtained from the U.S. Patent and Trademark Office, and compare its performance with that of the three conventional methods. The results demonstrate that the proposed patent-network-based approach yields more accurate class predictions than the patent network-based approach.
    Date
    22. 1.2011 13:04:21
  2. Kronegger, L.; Mali, F.; Ferligoj, A.; Doreian, P.: Classifying scientific disciplines in Slovenia : a study of the evolution of collaboration structures (2015) 0.05 
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    Abstract
    We explore classifying scientific disciplines including their temporal features by focusing on their collaboration structures over time. Bibliometric data for Slovenian researchers registered at the Slovenian Research Agency were used. These data were obtained from the Slovenian National Current Research Information System. We applied a recently developed hierarchical clustering procedure for symbolic data to the coauthorship structure of scientific disciplines. To track temporal changes, we divided data for the period 1986-2010 into five 5-year time periods. The clusters of disciplines for the Slovene science system revealed 5 clusters of scientific disciplines that, in large measure, correspond with the official national classification of sciences. However, there were also some significant differences pointing to the need for a dynamic classification system of sciences to better characterize them. Implications stemming from these results, especially with regard to classifying scientific disciplines, understanding the collaborative structure of science, and research and development policies, are discussed.
    Date
    21. 1.2015 14:55:22
  3. Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014) 0.04 
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    Abstract
    This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
  4. Ridenour, L.: Boundary objects : measuring gaps and overlap between research areas (2016) 0.04 
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    Abstract
    The aim of this paper is to develop methodology to determine conceptual overlap between research areas. It investigates patterns of terminology usage in scientific abstracts as boundary objects between research specialties. Research specialties were determined by high-level classifications assigned by Thomson Reuters in their Essential Science Indicators file, which provided a strictly hierarchical classification of journals into 22 categories. Results from the query "network theory" were downloaded from the Web of Science. From this file, two top-level groups, economics and social sciences, were selected and topically analyzed to provide a baseline of similarity on which to run an informetric analysis. The Places & Spaces Map of Science (Klavans and Boyack 2007) was used to determine the proximity of disciplines to one another in order to select the two disciplines use in the analysis. Groups analyzed share common theories and goals; however, groups used different language to describe their research. It was found that 61% of term words were shared between the two groups.
  5. Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011) 0.03 
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    Abstract
    The Impact Factors (IFs) of the Institute for Scientific Information suffer from a number of drawbacks, among them the statistics-Why should one use the mean and not the median?-and the incomparability among fields of science because of systematic differences in citation behavior among fields. Can these drawbacks be counteracted by fractionally counting citation weights instead of using whole numbers in the numerators? (a) Fractional citation counts are normalized in terms of the citing sources and thus would take into account differences in citation behavior among fields of science. (b) Differences in the resulting distributions can be tested statistically for their significance at different levels of aggregation. (c) Fractional counting can be generalized to any document set including journals or groups of journals, and thus the significance of differences among both small and large sets can be tested. A list of fractionally counted IFs for 2008 is available online at http:www.leydesdorff.net/weighted_if/weighted_if.xls The between-group variance among the 13 fields of science identified in the U.S. Science and Engineering Indicators is no longer statistically significant after this normalization. Although citation behavior differs largely between disciplines, the reflection of these differences in fractionally counted citation distributions can not be used as a reliable instrument for the classification.
    Date
    22. 1.2011 12:51:07
  6. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.02 
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    Date
    18. 3.2014 19:13:22
  7. Waltman, L.; Eck, N.J. van: ¬A new methodology for constructing a publication-level classification system of science : keyword maps in Google scholar citations (2012) 0.02 
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    Abstract
    Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular classification system. However, journal-level classification systems have two important limitations: They offer only a limited amount of detail, and they have difficulties with multidisciplinary journals. To avoid these limitations, we introduce a new methodology for constructing classification systems at the level of individual publications. In the proposed methodology, publications are clustered into research areas based on citation relations. The methodology is able to deal with very large numbers of publications. We present an application in which a classification system is produced that includes almost 10 million publications. Based on an extensive analysis of this classification system, we discuss the strengths and the limitations of the proposed methodology. Important strengths are the transparency and relative simplicity of the methodology and its fairly modest computing and memory requirements. The main limitation of the methodology is its exclusive reliance on direct citation relations between publications. The accuracy of the methodology can probably be increased by also taking into account other types of relations-for instance, based on bibliographic coupling.
  8. Gómez-Núñez, A.J.; Vargas-Quesada, B.; Moya-Anegón, F. de: Updating the SCImago journal and country rank classification : a new approach using Ward's clustering and alternative combination of citation measures (2016) 0.02 
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    Abstract
    This study introduces a new proposal to refine the classification of the SCImago Journal and Country Rank (SJR) platform by using clustering techniques and an alternative combination of citation measures from an initial 18,891 SJR journal network. Thus, a journal-journal matrix including simultaneously fractionalized values of direct citation, cocitation, and coupling was symmetrized by cosine similarity and later transformed into distances before performing clustering. The results provided a new cluster-based subject structure comprising 290 clusters that emerge by executing Ward's clustering in two phases and using a mixed labeling procedure based on tf-idf scores of the original SJR category tags and significant words extracted from journal titles. In total, 13,716 SJR journals were classified using this new cluster-based scheme. Although more than 5,000 journals were omitted in the classification process, the method produced a consistent classification with a balanced structure of coherent and well-defined clusters, a moderated multiassignment of journals, and a softer concentration of journals over clusters than in the original SJR categories. New subject disciplines such as "nanoscience and nanotechnology" or "social work" were also detected, providing evidence of good performance of our approach in refining the journal classification and updating the subject classification structure.
  9. Moohebat, M.; Raj, R.G.; Kareem, S.B.A.; Thorleuchter, D.: Identifying ISI-indexed articles by their lexical usage : a text analysis approach (2015) 0.02 
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    Abstract
    This research creates an architecture for investigating the existence of probable lexical divergences between articles, categorized as Institute for Scientific Information (ISI) and non-ISI, and consequently, if such a difference is discovered, to propose the best available classification method. Based on a collection of ISI- and non-ISI-indexed articles in the areas of business and computer science, three classification models are trained. A sensitivity analysis is applied to demonstrate the impact of words in different syntactical forms on the classification decision. The results demonstrate that the lexical domains of ISI and non-ISI articles are distinguishable by machine learning techniques. Our findings indicate that the support vector machine identifies ISI-indexed articles in both disciplines with higher precision than do the Naïve Bayesian and K-Nearest Neighbors techniques.
  10. Xu, F.; Liu, W.B.; Mingers, J.: New journal classification methods based on the global h-index (2015) 0.01 
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    Abstract
    In this work we develop new journal classification methods based on the h-index. The introduction of the h-index for research evaluation has attracted much attention in the bibliometric study and research quality evaluation. The main purpose of using an h-index is to compare the index for different research units (e.g. researchers, journals, etc.) to differentiate their research performance. However the h-index is defined by only comparing citations counts of one's own publications, it is doubtful that the h index alone should be used for reliable comparisons among different research units, like researchers or journals. In this paper we propose a new global h-index (Gh-index), where the publications in the core are selected in comparison with all the publications of the units to be evaluated. Furthermore, we introduce some variants of the Gh-index to address the issue of discrimination power. We show that together with the original h-index, they can be used to evaluate and classify academic journals with some distinct advantages, in particular that they can produce an automatic classification into a number of categories without arbitrary cut-off points. We then carry out an empirical study for classification of operations research and management science (OR/MS) journals using this index, and compare it with other well-known journal ranking results such as the Association of Business Schools (ABS) Journal Quality Guide and the Committee of Professors in OR (COPIOR) ranking lists.
  11. Perianes-Rodriguez, A.; Ruiz-Castillo, J.: ¬The impact of classification systems in the evaluation of the research performance of the Leiden Ranking universities (2018) 0.01 
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    Abstract
    In this article, we investigate the consequences of choosing different classification systems-namely, the way publications (or journals) are assigned to scientific fields-for the ranking of research units. We study the impact of this choice on the ranking of 500 universities in the 2013 edition of the Leiden Ranking in two cases. First, we compare a Web of Science (WoS) journal-level classification system, consisting of 236 subject categories, and a publication-level algorithmically constructed system, denoted G8, consisting of 5,119 clusters. The result is that the consequences of the move from the WoS to the G8 system using the Top 1% citation impact indicator are much greater than the consequences of this move using the Top 10% indicator. Second, we compare the G8 classification system and a publication-level alternative of the same family, the G6 system, consisting of 1,363 clusters. The result is that, although less important than in the previous case, the consequences of the move from the G6 to the G8 system under the Top 1% indicator are still of a large order of magnitude.
  12. Scholarly metrics under the microscope : from citation analysis to academic auditing (2015) 0.01 
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    Date
    22. 1.2017 17:12:50
  13. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01 
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    Date
    22. 8.2014 17:05:18
  14. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.01 
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    Date
    20. 1.2019 11:22:31
  15. Yan, E.: Finding knowledge paths among scientific disciplines (2014) 0.01 
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    Date
    26.10.2014 20:22:22
  16. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.01 
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    Date
    20. 1.2015 18:30:22
    17. 9.2018 18:22:23
  17. Wainer, J; Przibisczki de Oliveira, H.; Anido, R.: Patterns of bibliographic references in the ACM published papers (2011) 0.01 
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    Abstract
    This paper analyzes the bibliographic references made by all papers published by ACM in 2006. Both an automatic classification of all references and a human classification of a random sample of them resulted that around 40% of the references are to conference proceedings papers, around 30% are to journal papers, and around 8% are to books. Among the other types of documents, standards and RFC correspond to 3% of the references, technical and other reports correspond to 4%, and other Web references to 3%. Among the documents cited at least 10 times by the 2006 ACM papers, 41% are conferences papers, 37% are books, and 16% are journal papers.
  18. Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011) 0.01 
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    Date
    22. 1.2011 12:53:00
  19. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.01 
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    22. 1.2011 13:02:21
  20. Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013) 0.01 
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    Date
    22. 3.2013 14:04:09

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