A computer system for big scientometrics at the age of the World Wide Web

Grivel, Luc; Polanco, Xavier; Kaplan, Abdullah

doi:10.1007/bf02459296

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…The present research takes a quantitative approach, based first on descriptive statistics from the mainly bibliometric sources and further science mapping analysis. Borgman and Furner [102], Grivel, Polanco, and Kaplan [103], Santhanakarthikeyan, Padma, Veeramani, and Ravikrishnan [104] agree that bibliometrics and science mapping are a set of methods for quantitatively analyzing scientific literature. Among the works that use bibliometrics and science mapping are those of Garfield [105], who proposes a bibliographic system for the study of articles, based on its relevance and citation index.…”

Section: Methodsmentioning

confidence: 99%

Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability

et al. 2019

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The tracking of tourist movements is an essential aspect in the management of sustainable tourist destinations. The current information and communication technologies provide innovative ways of collecting data on tourist movements, but it is still necessary to evaluate tools and methods of study for this challenge. At this point, mobile technologies are the best candidate for this task. Given the relevance of the topic, this paper proposes a mapping science analysis of publications on "movement of tourists" and "traceability." It has been carried out in the two main sources WOS and SCOPUS. The term "traceability" is brought from industry and technology areas to be applied to the tourist movement/mobility tracking and management. The methodological scheme is based on a selection of search criteria with combinations of terms. The sources of specialized information in applied social sciences and technology were then selected. From there, the searches have been executed for their subsequent analysis in three stages-(I) relevance analysis filtering the results to obtain the most pertinent; (II) analysis of articles with similarity thematic, authors, journals or citations; (III) analysis of selected papers as input for the mapping analysis using Citespace. The automatic naming of clusters under the selected processing confirms that the analysis of movements is a valid scientific trend but research-oriented from the perspective of traceability is non-existent, so this approach is novel and complementary to existing ones and a potential contribution to knowledge about tourist movements. Finally, a set of methodological considerations and a classification of information capture tools are proposed. In this classification, mobile technology is the best option to enable tourist movement analysis.

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Section: Methodsmentioning

confidence: 99%

Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability

et al. 2019

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“…Analyzing all the papers requires advanced computer definitions (Grivel, Polanco, & Kaplan, 1997). That is why the analysis has been limited to a significant number of papers.…”

Section: Paper Selectionmentioning

confidence: 99%

Influential WoS indexed papers on Food Technology domain in 2015: An overview of the current influences of Food technology research

Turki¹,

Jalali²

2017

Preprint

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In this research paper, we analyzed the hy-core of Food technology Thomson Reuters Web of Science indexed papers for the year 2015 using Bibliometric and Scientometric techniques to obtain an overview about the main journals, institutions, authors and countries that influence the most Food technology research area nowadays. This study confirmed that the main papers that currently influences Food technology research are either new papers defining innovative techniques and findings or old papers that are mainly cited because they are considered as fundamental in the field by the Food technology research communities. It also proved a major current influence of the old highly cited researchers, of the specialized nationwide research institutes, of the journals with high impact factors that publish papers about all the aspects of Food technology research, and of the United States specifically University of Massachusetts Amherst on Food technology research.

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“…These applications also exist on a CD-ROM version (dmcontact@inist.fr). In addition, these applications can be accessed and searched with HENOCH system over the Internet (Grivel et al 1997). …”

Section: Automatic Hypertext Generationmentioning

confidence: 99%

Artificial neural network technology for the classification and cartography of scientific and technical information

1998

Self Cite

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This paper describes the implementation of multivariate data analysis: NEURODOC applies the axial k-means method for automatic, non-hierarchical cluster analysis and a Principal Component Analysis (PCA) for representing the clusters on a map. We next introduce Artificial Neural Networks (ANNs) to extend NEURODOC into a neural platform for the cluster analysis and cartography of bibliographic data. The ANNs tested are: the Adaptive Resonance Theory (ART 1), a Multilayer Perceptron (MLP), and an associative network with unsupervised learning (KOHONEN). This platform is intended for quantitative analysis of information.

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A computer system for big scientometrics at the age of the World Wide Web

Cited by 5 publications

References 6 publications

Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability

Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability

Influential WoS indexed papers on Food Technology domain in 2015: An overview of the current influences of Food technology research

Artificial neural network technology for the classification and cartography of scientific and technical information

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