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Artificial Intelligence in Concrete Materials
Published in M.Z. Naser, Leveraging Artificial Intelligence in Engineering, Management, and Safety of Infrastructure, 2023
Zhanzhao Li, Aleksandra Radlińska
Keywords are the words or phrases that deliver the most essential content of a published document (Martinez et al., 2019; Pan and Zhang, 2021). The analysis of keywords can offer opportunities to uncover the main research interests in any scientific field (Darko et al., 2020; van Eck and Waltman, 2014). In order to construct and map the knowledge domain between AI and concrete materials, a keyword co-occurrence network was developed using VOS viewer (van Eck and Waltman, 2013). The co-occurrence of two keywords can be defined as the situation when both keywords occur together in a publication (van Eck and Waltman, 2014). A typical co-occurrence network of keywords consists of nodes (i.e., keywords) and links (indicating relations between pairs of nodes). The strength of the relation between two keywords represents the connection of their respective knowledge domains. Visualization of the keyword co-occurrence network provides an understanding of existing research topics and how they are intellectually developed and connected (van Eck and Waltman, 2014).
Reshaping Tourist Experience with AI-Enabled Technologies: A Comprehensive Review and Future Research Agenda
Published in International Journal of Human–Computer Interaction, 2023
Rijul Chaturvedi, Sanjeev Verma, Faizan Ali, Satish Kumar
Co-occurrence network analysis identifies emerging themes, analyses the strength of the relationship between various themes, and exhibits trends in the research field by analyzing the author’s keywords’ network (Donthu, Kumar, Mukherjee, et al., 2021). This section identifies the main themes (see Table 5) in the literature on tourist experience with artificial intelligence. These themes are identified using network indicators such as Degree (DG), occurrences (OC), average publication year (APY), and the average number of citations (AC). Figure 4 presents the keyword co-occurrence network retrieved using VOSviewer with seven colours of clusters, including big data analytics, text analytics, smart tourism, virtual tourism, social media, customer experience, and semantic analysis. In addition, Figure 5 represents the word cloud formation of author keywords in Biblioshiny R software.
A Review of machine learning techniques for wind turbine’s fault detection, diagnosis, and prognosis
Published in International Journal of Green Energy, 2023
Prince Waqas Khan, Yung-Cheol Byun
We used VOSViewer to discuss the concepts that appeared most frequently in the chosen articles. VOSviewer is a piece of software designed to assist in the creation of bibliometric networks as well as their visualization Van Eck and Waltman (2010). It also provides text-mining functionality. We have used it to construct and visualize co-occurrence networks of important terms extracted from a body of scientific literature. These networks are constructed using the data obtained from the text mining of the downloaded articles. Figure 4 shows the co-occurrence network visualization of keywords. These keywords consist of various terms, including SCADA data, fault detection, diagnosis, principal component analysis reliability, structural health monitoring, and several others.
Transport research under Belt and Road Initiative: current trends and future research agenda
Published in Transportmetrica A: Transport Science, 2021
Xueqin Wang, Yiik Diew Wong, Kevin X. Li, Kum Fai Yuen
Phrases such as port facilities, consolidation centres, transport infrastructures, were identified in a few articles. Given their similar connotations, they were compiled into one research theme termed logistics infrastructure. On the other hand, some similar phrases were purposely categorised under different themes despite their similarity. For example, land bridge and high-speed railway were listed as separate themes. While land bridge is essentially high-speed railway, it was often examined as an integrated part of intermodal transportation. High-speed railway, on the other hand, is often evaluated as a stand-alone mode of transportation. Table 3 lists key research themes that frequently appeared in articles selected. Based on their occurrences, logistics infrastructure, alternative route, and China-Europe emerged the most popular themes investigated by researchers. A total of 28 themes appeared in at least two of the articles reviewed. These 28 themes as well as their associated strengths were used as a basis for co-occurrence network analysis. The next section provides detailed elaborations on the four research trends based on co-occurrence network analysis.