Search (120 results, page 6 of 6)

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Abstract

Automated methods for the analysis, modeling, and visualization of large-scale scientometric data provide measures that enable the depiction of the state of world scientific development. We aimed to integrate minimum span clustering (MSC) and minimum spanning tree methods to cluster and visualize the global pattern of scientific publications (PSP) by analyzing aggregated Science Citation Index (SCI) data from 1994 to 2011. We hypothesized that PSP clustering is mainly affected by countries' geographic location, ethnicity, and level of economic development, as indicated in previous studies. Our results showed that the 100 countries with the highest rates of publications were decomposed into 12 PSP groups and that countries within a group tended to be geographically proximal, ethnically similar, or comparable in terms of economic status. Hubs and bridging nodes in each knowledge production group were identified. The performance of each group was evaluated across 16 knowledge domains based on their specialization, volume of publications, and relative impact. Awareness of the strengths and weaknesses of each group in various knowledge domains may have useful applications for examining scientific policies, adjusting the allocation of resources, and promoting international collaboration for future developments.

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Date

8. 4.2015 16:20:29

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Date

27. 5.2022 18:19:29

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Theme

Klassifikationssysteme im Online-Retrieval

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Footnote

Original in: Classification research: Proceedings of the Second International Study Conference held at Hotel Prins Hamlet, Elsinore, Denmark, 14th-18th Sept. 1964. Ed.: Pauline Atherton. Copenhagen: Munksgaard 1965. S.295-310.

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Content

As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.

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Series

Report NAG9-551, No. 92-1

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Abstract

Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.

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Source

Machine learning. 87(2012) no.1, S.33-55

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Abstract

In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI-JCR category cocitation and social networks analysis through the use of the Pathfinder algorithm has demonstrated its ability to achieve high quality, schematic visualizations for these kinds of domains. Now, the next step would be to generate these scientograms in an on-line fashion. To do so, there is a need to significantly decrease the run time of the latter pruning technique when working with category cocitation matrices of a large dimension like the ones handled in these large domains (Pathfinder has a time complexity order of O(n4), with n being the number of categories in the cocitation matrix, i.e., the number of nodes in the network). Although a previous improvement called Binary Pathfinder has already been proposed to speed up the original algorithm, its significant time complexity reduction is not enough for that aim. In this paper, we make use of a different shortest path computation from classical approaches in computer science graph theory to propose a new variant of the Pathfinder algorithm which allows us to reduce its time complexity in one order of magnitude, O(n3), and thus to significantly decrease the run time of the implementation when applied to large scientific domains considering the parameter q = n - 1. Besides, the new algorithm has a much simpler structure than the Binary Pathfinder as well as it saves a significant amount of memory with respect to the original Pathfinder by reducing the space complexity to the need of just storing two matrices. An experimental comparison will be developed using large networks from real-world domains to show the good performance of the new proposal.

Date

1. 8.2008 12:44:35

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Source

Journal of the American Society for Information Science and Technology. 58(2007) no.1, S.25-38

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Date

1. 1.2009 9:57:50

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Date

1. 1.2009 10:01:15

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Source

Journal of the American Society for Information Science and Technology. 60(2009) no.1, S.90-110

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Abstract

This article aims to stimulate research on business process oriented knowledge infrastructures by pointing to the power of visualizations. It claims that business process oriented knowledge infrastructure research is stuck and therefore needs to reinvent and revitalize itself with new impulses. One such stimulus is the use of visualization techniques in business process oriented knowledge infrastructures, with the aim to improve knowledge transfer, knowledge communication, and knowledge creation. First, this article presents an overview on related visualization research. Second, it proposes the Knowledge Visualization Framework as a theoretical backbone where business process oriented knowledge infrastructure research can anchor itself. The framework points to the key questions that need to be answered when visual methods are used in business process oriented knowledge infrastructures. Finally, the article compares the Tube Map Visualization with the Gantt Chart, and proves that the new format excels the traditional approach in regards to various tasks. The findings from the evaluation of 44 interviews indicates that the Project Tube Map is more effective for (1) drawing attention and keeping interest, (2) presenting overview and detail, (3) visualizing who is collaborating with whom, (4) motivating people to participate in the project, and (5) increasing recall. The results presented in this paper are important for researchers and practitioners in the fields of Knowledge Management, Knowledge Visualization, Project Management, and Visual Communication Sciences.

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Abstract

This book is the outcome of the Dagstuhl Seminar on "Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation" held at Dagstuhl Castle, Germany, from May 28 to June 1, 2007. Information Visualization (InfoVis) is a relatively new research area, which focuses on the use of visualization techniques to help people understand and analyze data.This book documents and extends the findings and discussions of the various sessions in detail. The seven contributions cover the most important topics: Part I is on general reflections on the value of information visualization; evaluating information visualizations; theoretical foundations of information visualization; teaching information visualization. Part II deals with specific aspects on creation and collaboration: engaging new audiences for information visualization; process and pitfalls in writing information visualization research papers; and visual analytics: definition, process, and challenges.

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Source

Journal of the Association for Information Science and Technology. 68(2017) no.1, S.154-167

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Abstract

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.

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Abstract

This research takes the academic articles in the Web of Science's core collection database as a corpus to draw a series of knowledge maps, to explore the relationships, connectivity, dis-tribution, and evolution among their keywords with respect to smart cities in the last decade. Beyond just drawing a text cloud or measuring their sizes, we further explore their texture by iden-tifying the hottest keywords in academic articles, construct links between and among them that share common keywords, identify islands, rocks, reefs that are formed by connected articles-a metaphor inspired by Ong et al. (2005)-and analyze trends in their evolution. We found the following phenomena: 1) "Internet of Things" is the most frequently mentioned keyword in recent research articles; 2) the numbers of islands and reefs are increas-ing; 3) the evolutions of the numbers of weighted links have frac-tal-like structure; and, 4) the coverage of the largest rock, formed by articles that share a common keyword, in the largest island is converging into around 10% to 20%. These phenomena imply that a common interest in the technology of smart cities has been emerging among researchers. However, the administrative, social, economic, and cultural issues need more attention in academia in the future.

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Date

1. 2.1997 9:16:32