Analysis of Erdös Collaboration Graph and the Paper Citation Network

2014 ◽  
Author(s):  
Chengrui Yang ◽  
Xiaohui Cui ◽  
Xiaoyong Sun ◽  
Yuanda Diao ◽  
Shuai Wang ◽  
...  
Keyword(s):  
Citation Network ◽  
Paper Citation

On the growth of directed complex networks with preferential attachment: Effect upon the prohibition of multiple links

2015 ◽  
Vol 26 (06) ◽  
pp. 1550066 ◽  
Author(s):  
J. Esquivel-Gómez ◽  
R. E. Balderas-Navarro ◽  
Edgardo Ugalde ◽  
J. Acosta-Elías
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Preferential Attachment ◽  
Citation Network ◽  
Topological Properties ◽  
The World ◽  
Single Link ◽  
Paper Citation ◽  
Real Complex ◽  
Connectivity Distribution

Several real-world directed networks do not have multiple links. For example, in a paper citation network a paper does not cite two identical references, and in a network of friends there exists only a single link between two individuals. This suggest that the growth and evolution models of complex networks should take into account such feature in order to approximate the topological properties of this class of networks. The aim of this paper is to propose a growth model of directed complex networks that takes into account the prohibition of the existence multiple links. It is shown through numerical experiments that when multiple links are forbidden, the exponent γ of the in-degree connectivity distribution, [Formula: see text], takes values ranging from 1 to ∞. In particular, the proposed multi-link free (MLF) model is able to predict exponents occurring in real-world complex networks, which range 1.05 < γ < 3.51. As an example, the MLF reproduces somxe topological properties exhibited by the network of flights between airports of the world (NFAW); i.e. γ ≈ 1.74. With this result, we believe that the multiple links prohibition might be one of the local processes accounting for the existence of exponents γ < 2 found in some real complex networks.

scholarly journals Link prediction in paper citation network to construct paper correlation graph

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Hanwen Liu ◽  
Huaizhen Kou ◽  
Chao Yan ◽  
Lianyong Qi
Keyword(s):  
Recommender System ◽  
Real World ◽  
Link Prediction ◽  
Citation Network ◽  
Experimental Results ◽  
The Real ◽  
Correlation Graph ◽  
Paper Citation ◽  
Prediction Approach

Abstract Nowadays, recommender system has become one of the main tools to search for users’ interested papers. Since one paper often contains only a part of keywords that a user is interested in, recommender system returns a set of papers that satisfy the user’s need of keywords. Besides, to satisfy the users’ requirements of further research on a certain domain, the recommended papers must be correlated. However, each paper of an existing paper citation network hardly has cited relationships with others, so the correlated links among papers are very sparse. In addition, while a mass of research approaches have been put forward in terms of link prediction to address the network sparsity problems, these approaches have no relationship with the effect of self-citations and the potential correlations among papers (i.e., these correlated relationships are not included in the paper citation network as their published time is close). Therefore, we propose a link prediction approach that combines time, keywords, and authors’ information and optimizes the existing paper citation network. Finally, a number of experiments are performed on the real-world Hep-Th datasets. The experimental results demonstrate the feasibility of our proposal and achieve good performance.

A Review of Minimum Quantity Lubrication (MQL) based on Bibliometry

2020 ◽  
Vol 13 ◽  
Author(s):  
Gaurav Gaurav ◽  
Abhay Sharma ◽  
G S Dangayach ◽  
M L Meena
Keyword(s):  
Descriptive Analysis ◽  
Minimum Quantity Lubrication ◽  
Citation Network ◽  
Machining Process ◽  
Cutting Fluid ◽  
Future Research ◽  
Research Directions ◽  
Minimum Quantity ◽  
Research Areas ◽  
Future Research Directions

Background: Minimum quantity lubrication (MQL) is one of the most promising machining techniques that can yield a reduction in consumption of cutting fluid more than 90 % while ensuring the surface quality and tool life. The significance of the MQL in machining makes it imperative to consolidate and analyse the current direction and status of research in MQL. Objective: This study aims to assess global research publication trends and hot topics in the field of MQL among machining process. The bibliometric and descriptive analysis are the tools that the investigation aims to use for the data analysis of related literature collected from Scopus databases. Methods: Various performance parameters are extracted, such as document types and languages of publication, annual scientific production, total documents, total citations, and citations per article. The top 20 of the most relevant and productive sources, authors, affiliations, countries, word cloud, and word dynamics are assessed. The graphical visualisation of the bibliometric data is presented in terms of bibliographic coupling, citation, and co-citation network. Results: The investigation reveals that the International Journal of Machine Tools and Manufacture (2611 citations, 31 hindex) is the most productive journal that publishes on MQL. The most productive institution is the University of Michigan (32 publications), the most cited country is Germany (1879 citations), and the most productive country in MQL is China (124 publications). The study shows that ‘Cryogenic Machining’, ‘Sustainable Machining’, ‘Sustainability’, ‘Nanofluid’ and ‘Titanium alloy’ are the most recent keywords and indications of the hot topics and future research directions in the MQL field. Conclusion: The analysis finds that MQL is progressing in publications and the emerging with issues that are strongly associated with the research. This study is expected to help the researchers to find the most current research areas through the author’s keywords and future research directions in MQL and thereby expand their research interests.

scholarly journals Biomedical articles share annotations with their citation neighbors

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Raul Rodriguez-Esteban
Keyword(s):  
Knowledge Management ◽  
Large Scale ◽  
Citation Network

Abstract Background Numerous efforts have been poured into annotating the wealth of knowledge contained in biomedical articles. Thanks to such efforts, it is now possible to quantitatively explore relations between these annotations and the citation network at large scale. Results With the aid of several large and small annotation databases, this study shows that articles share annotations with their citation neighborhood to the point that the neighborhood’s most common annotations are likely to be those appearing in the article. Conclusions These findings posit that an article’s citation neighborhood defines to a large extent the article’s annotated content. Thus, citations should be considered as a foundation for future knowledge management and annotation of biomedical articles.

scholarly journals Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research

AI & Society ◽  
2021 ◽  
Author(s):  
Milad Mirbabaie ◽  
Lennart Hofeditz ◽  
Nicholas R. J. Frick ◽  
Stefan Stieglitz
Keyword(s):  
Artificial Intelligence ◽  
Citation Network ◽  
Status Quo ◽  
Biomedical Ethics ◽  
Future Research ◽  
Ethical Considerations ◽  
Ethical Discourse ◽  
The Status ◽  
Clinical Environments ◽  
Research Questions

AbstractThe application of artificial intelligence (AI) in hospitals yields many advantages but also confronts healthcare with ethical questions and challenges. While various disciplines have conducted specific research on the ethical considerations of AI in hospitals, the literature still requires a holistic overview. By conducting a systematic discourse approach highlighted by expert interviews with healthcare specialists, we identified the status quo of interdisciplinary research in academia on ethical considerations and dimensions of AI in hospitals. We found 15 fundamental manuscripts by constructing a citation network for the ethical discourse, and we extracted actionable principles and their relationships. We provide an agenda to guide academia, framed under the principles of biomedical ethics. We provide an understanding of the current ethical discourse of AI in clinical environments, identify where further research is pressingly needed, and discuss additional research questions that should be addressed. We also guide practitioners to acknowledge AI-related benefits in hospitals and to understand the related ethical concerns.

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