Analysis of Patterns in the University World Rankings Webometrics, Shanghai, QS and SIR-SCimago: Case Latin America

Torres-Samuel, Maritza; Vásquez, Carmen; Viloria, Amelec; Varela, Noel; Hernández–Fernández, Lissette; Portillo-Medina, Rafael

doi:10.1007/978-3-319-93803-5_18

Cited by 39 publications

(16 citation statements)

References 2 publications

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“…(2) its use in various bibliometric studies [57][58][59]; and (3) it is the source of information for the QS World University Rankings, the ranking most used by Latin American universities to determine their position in the region and the world [60,61].…”

Section: Database Selection Initial Search and Document Compilationmentioning

confidence: 99%

Scientific Research in Ecuador: A Bibliometric Analysis

et al. 2021

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Ecuador has shown a growth in its scientific production since 2011, representing 85% of the total historical production. These investigations are reflected in scientific publications, which address world interest topics and serve as a link for the university, business, and society. This work aims to analyze the scientific production generated by Ecuador in the period of 1920–2020 using bibliometric methods to evaluate its intellectual structure and performance. The methodology applied in this study includes: (i) terms definition and search criteria; (ii) database selection, initial search, and document compilation; (iii) data extraction and software selection; and finally, (iv) analysis of results. The results show that scientific production has been consolidated in 30,205 documents, developed in 27 subject areas, in 13 languages under the contribution of 84 countries. This intellectual structure is in harmony with the global context when presenting research topics related to “Biology and regional climate change”, “Higher education and its various approaches”, “Technology and Computer Science”, “Medicine”, “Energy, food and water”, and ”Development and applications on the Web”. Topics framed in the Sustainable Development Goals (SDGs), sustainability, climate change, and others. This study contributes to the academic community, considering current re-search issues and global concerns, the collaboration between universities and countries that allow establishing future collaboration links.

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Section: Database Selection Initial Search and Document Compilationmentioning

confidence: 99%

Scientific Research in Ecuador: A Bibliometric Analysis

et al. 2021

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“…The proposed method shows the best lowest clustering results and outperforms in a few prior researches [20], [21] and [22]. As indicated in Table 7, all existing methods have their complexity using evolutionary strategy automatic clustering methods for determining the number of clusters automatically in k-means, while the proposed method uses technical-statistical control for problem-solving of ACDE as an automatic clustering strategy for finding the optimal number of clusters in k-means method.…”

Section: Data Transformation Stagementioning

confidence: 91%

RETRACTED CHAPTER: U-Control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k-Means

Silva

Lezama

Varela

et al. 2019

Green, Pervasive, and Cloud Computing

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The automatic clustering differential evolution (ACDE) is one of the clustering methods that are able to determine the cluster number automatically. However, ACDE still makes use of the manual strategy to determine k activation threshold thereby affecting its performance. In this study, the ACDE problem will be ameliorated using the u-control chart (UCC) then the cluster number generated from ACDE will be fed to k-means. The performance of the proposed method was tested using six public datasets from the UCI repository about academic efficiency (AE) and evaluated with Davies Bouldin Index (DBI) and Cosine Similarity (CS) measure. The results show that the proposed method yields excellent performance compared to prior researches.

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“…The society in this case consists of prospective students, prospective staff, and the stakeholders who want to get to know each other better to establish synergy and become part of the university. A website is a crucial tool for universities because it is still considered an effective medium for publishing the most recent official information [1] and building brand recognition, especially for positions in international competition [1]- [3].…”

Section: Introductionmentioning

confidence: 99%

Relational Data Model on The University Website with Search Engine Optimization

Alifi

Hayati²,

Wonoseto³

2022

IJID

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The visibility of a university’s website on the search engine becomes an essential factor to reach a wider audience. One way to improve the visibility of a website is through Search Engine Optimization (SEO). University’s website development with SEO is inseparable from the data model because SEO supporting factors are parts of the consideration in the components and structure of the data model. This study aims to build a data model for a university website accompanied by SEO. The relational data model is used in this study based on the performance and maturity in defining schema-based design. This study was conducted through four sequential stages: literature review, planning, implementation, and evaluation. The resulting relational data model is one that has accommodated four supporting factors for SEO, namely Meta description, Meta keywords, URL structure, and image description. This study has succeeded in building a relational data model at the abstraction level of conceptual and logical. In the conceptual data model, one entity and 11 attributes are formed. The logical data model was implemented in independent work environments using RelaX and operational requirements can be fulfilled by representing each table or relationship in the schema using relational algebra.

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Analysis of Patterns in the University World Rankings Webometrics, Shanghai, QS and SIR-SCimago: Case Latin America

Cited by 39 publications

References 2 publications

Scientific Research in Ecuador: A Bibliometric Analysis

Scientific Research in Ecuador: A Bibliometric Analysis

RETRACTED CHAPTER: U-Control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k-Means

Relational Data Model on The University Website with Search Engine Optimization

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