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Scientometrics
Authors: Thomas Gurney, Edwin Horlings, and Peter van den Besselaar

)—where variance in names is substantially lower—reinforce the need for an automated approach to author disambiguation. There is a need for algorithms designed to extract patterns of similarity from different variables, patterns that can set one

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industries require more technologies for individual products (Carree et al. 2000 ). Thus, an automated method is necessary to support experts. In fact, various factors such as patentability, technological similarity, and scope of claims should be

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Introduction In several scientific areas—like ecology, information retrieval, machine learning, psychology and scientometrics—the measurement of similarity between objects plays a role. In scientometrics, examples of considered

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science, technology and society. The field of ecology has a long tradition of studies related to diversity. Consequently, there exists an extensive literature on measures of diversity within populations/communities and dissimilarity or similarity

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reliable. However, the analysis of patents on the basis of combined concepts gives rise to three questions for research: How can combined concepts be extracted and built from patents? How can textual similarities between patents be assessed on the basis of

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asking researchers to rate the papers they read, and so on. Finally, inter-researcher similarity measures are calculated on these data to identify the scientists sharing most interests with the user of the SLRS. Although mature and appealing in

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Abstract  

Journals covered by the 2006 Science Citation Index Journal Citation Reports database have been subjected to a clustering procedure utilizing h-similarity as the underlying similarity measure. Clustering complemented with a prototyping routine provided well-conceivable results that are both compatible with and further refine existing taxonomies of science.

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Abstract  

Hirsch’s concept of h-index was used to define a similarity measure for journals. The h-similarity is easy to calculate from the publicly available data of the Journal Citation Reports, and allows for plausible interpretation. On the basis of h-similarity, a relative eminence indicator of journals was determined: the ratio of the JCR impact factor to the weighted average of that of similar journals. This standardization allows journals from disciplines with lower average citation level (mathematics, engineering, etc.) to get into the top lists.

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Abstract  

The measurement of textual patent similarities is crucial for important tasks in patent management, be it prior art analysis, infringement analysis, or patent mapping. In this paper the common theory of similarity measurement is applied to the field of patents, using solitary concepts as basic textual elements of patents. After unfolding the term ‘similarity’ in a content and formal oriented level and presenting a basic model of understanding, a segmented approach to the measurement of underlying variables, similarity coefficients, and the criteria-related profiles of their combinations is lined out. This leads to a guided way to the application of textual patent similarities, interesting both for theory and practice.

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Abstract  

This paper investigates the utility of the Inclusion Index, the Jaccard Index and the Cosine Index for calculating similarities of documents, as used for mapping science and technology. It is shown that, provided that the same content is searched across various documents, the Inclusion Index generally delivers more exact results, in particular when computing the degree of similarity based on citation data. In addition, various methodologies such as co-word analysis, Subject-Action-Object (SAO) structures, bibliographic coupling, co-citation analysis, and self-citation links are compared. We find that the two former ones tend to describe rather semantic similarities that differ from knowledge flows as expressed by the citation-based methodologies.

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