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issue recommendations. In “ Checking similarity measures against researchers’ perception of relatedness ” section, we define an evaluation protocol for measuring the accuracy of recommendations according to researchers’ perception. It allows us to assess

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Abstract  

Citations in five leading environmental science journals were examined for accuracy. 24.41% of the 2,650 citations checked were found to contain errors. The largest category of errors was in the author field. Of the five journals Conservation Biology had the lowest percentage of citations with errors and Climatic Change had the highest. Of the citations with errors that could be checked in Web of Science, 18.18% of the errors caused a search for the cited article to fail. Citations containing electronic links had fewer errors than those without.

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In this study, we examine and validate the use of existing text mining techniques (based on the vector space model and latent semantic indexing) to detect similarities between patent documents and scientific publications. Clearly, experts involved in domain studies would benefit from techniques that allow similarity to be detected—and hence facilitate mapping, categorization and classification efforts. In addition, given current debates on the relevance and appropriateness of academic patenting, the ability to assess content-relatedness between sets of documents—in this case, patents and publications—might become relevant and useful. We list several options available to arrive at content based similarity measures. Different options of a vector space model and latent semantic indexing approach have been selected and applied to the publications and patents of a sample of academic inventors (n = 6). We also validated the outcomes by using independently obtained validation scores of human raters. While we conclude that text mining techniques can be valuable for detecting similarities between patents and publications, our findings also indicate that the various options available to arrive at similarity measures vary considerably in terms of accuracy: some generally accepted text mining options, like dimensionality reduction and LSA, do not yield the best results when working with smaller document sets. Implications and directions for further research are discussed.

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Fejes Tóth [] studied approximations of smooth surfaces in three-space by piecewise flat triangular meshes with a given number of vertices on the surface that are optimal with respect to Hausdorff distance. He proves that this Hausdorff distance decreases inversely proportional with the number of vertices of the approximating mesh if the surface is convex. He also claims that this Hausdorff distance is inversely proportional to the square of the number of vertices for a specific non-convex surface, namely a one-sheeted hyperboloid of revolution bounded by two congruent circles. We refute this claim, and show that the asymptotic behavior of the Hausdorff distance is linear, that is the same as for convex surfaces.

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We compare a new method for measuring research leadership with the traditional method. Both methods are objective and reliable, utilize standard citation databases, and are easily replicated. The traditional method uses partitions of science based on journal categories, and has been extensively used to measure national leadership patterns in science, including those appearing in the NSF Science & Engineering Indicators Reports and in prominent journals such as Science and Nature. Our new method is based on co-citation techniques at the paper level. It was developed with the specific intent of measuring research leadership at a university, and was then extended to examine national patterns of research leadership. A comparison of these two methods provides compelling evidence that the traditional method grossly underestimates research leadership in most countries. The new method more accurately portrays the actual patterns of research leadership at the national level.

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-indexes about a linear relation are matched by similar deviations of the a -indexes about a linear relation, so the accuracy of the a -values is the same as that of the h -values. Fig. 5 The relation ( a = 1

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-review. We will support our position by comparing the two methodologies in terms of the essential parameters of any measurement system: accuracy, robustness, validity, functionality, time and costs ( Table 1 ). Table 1

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observations, and some do this better than others, providing a socially independent ‘measurement stick’ to their value. The interplay of social influences and accuracy and explanatory power of research is at the core of the simulations. Our goal is to

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the alternative methods in terms of computation time, while having an excellent accuracy (Blondel et al. 2008 ). The Louvain method has been employed in the analysis of scientific knowledge. Lambiotte and Panzarasa ( 2009 ) discussed the community

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