A Multi-Type Transferable Method for Missing Link Prediction in Heterogeneous Social Networks

Wang, Huan; Cui, Ziwen; Liu, Ruigang; Fang, Lei; Sha, Ying

doi:10.1109/tkde.2022.3233481

Cited by 43 publications

(20 citation statements)

References 44 publications

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“…According to institutional economics, enterprise networks, alongside market and bureaucracy, is one way of resource allocation. The enterprise network is comprised of nodal firms that are linked by complementary strengths and resource sharing [ 31 – 33 ]. Through the intimate interaction of nodes in an enterprise economic network, nodes can receive resources such as information and knowledge from the external environment [ 34 ].…”

Section: Methodology and Hypothesis Developmentmentioning

confidence: 99%

Do network synergies facilitates the realization of M&A motivation?: From the perspective of network node degree and strength change

Zhang

2023

PLoS ONE

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The current evaluation of M&A performance lacks consideration of M&A motives. In this paper, we theoretically analyse and empirically test the effect of network synergy generated by M&A on the degree of realization of corporate M&A motives and the mechanism of its effect by constructing an equity network between a listed company and its subsidiaries within the company. The results show that the greater the variation of internal network node degree and strength, the more beneficial it is to promote the degree of realization of corporate M&A motivation; the results of further mechanism of action tests show that the variation of network node degree and strength has significant effects on economies of scale, economies of scope, and transaction costs; Furthermore, the heterogeneity test finds that the effect of variation of network node degree and strength to promote the degree of realization of corporate M&A motivation is more significant in the case of non-cash payment method and related M&A. This paper extends the study of complex networks to the field of M&A and uniquely explains the paradox of the "high failure rate" of M&A and the increasing activity of M&A activities from the perspective of network synergy, which helps to rationalize the M&A behavior of enterprises and further regulate the M&A behavior of listed companies by regulatory authorities.

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Section: Methodology and Hypothesis Developmentmentioning

confidence: 99%

Do network synergies facilitates the realization of M&A motivation?: From the perspective of network node degree and strength change

Zhang

2023

PLoS ONE

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“…In a recent study conducted by ( Lelissa, 2020 ), the implications for the private banking sector in Ethiopia were examined, with a specific emphasis on the need for improved resource mobilization strategies following the COVID-19 pandemic. their recent publication titled ( Wang et al, 2023 ) shed light on the significant consequences of the global health crisis on businesses. The authors specifically emphasize the effects observed in Asian markets, highlighting the unique challenges faced by companies in this region.…”

Section: Literature Reviewmentioning

confidence: 99%

Digital threads in turbulent times: unraveling technostress and cleaner production in the food industry

Irfan,

Sulehri,

Manickiam

2024

Front. Robot. AI

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Introduction: In the current landscape marked by swift digital transformations and global disruptions, comprehending the intersection of digitalization and sustainable business practices is imperative. This study focuses on the food industries of China and Pakistan, aiming to explore the influence of digitalization on cleaner production.Methods: Employing a cross-sectional design, data were gathered through online surveys involving a diverse group of employees. Special attention was given to the emergent phenomenon of technostress and its subsequent implications for individuals in the workplace.Results: The findings of the study demonstrate a significant impact of digitalization on both resource mobilization and interaction quality within the surveyed food industries. Notably, technostress emerged as a mediating factor, shedding light on the psychological challenges associated with digital transitions. The study further reveals the moderating role of the COVID-19 pandemic, altering the dynamics among the variables under investigation.Discussion: From a theoretical perspective, this research contributes to the cleaner production literature by bridging it with the human-centric nuances of technological adaptation. On a practical level, the study emphasizes the importance of aligning digital strategies with resource mobilization to achieve sustainable outcomes. For the food industry and potentially beyond, the research offers a roadmap for integrating digital tools into operations, ensuring efficiency, and promoting cleaner production.

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“…Diagnostic radiologists use a variety of healthcare imaging modalities. The most broadly used to diagnose and identify illnesses were MRI, X-ray radiology, positronemission tomography, and computed tomography [93]. Radiologists use sets of images for disease screening, identifying the disease's cause, and monitoring patient progress.…”

Section: Radiology Applicationsmentioning

confidence: 99%

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors

Amiri,

Heidari,

Darbandi

et al. 2023

Sustainability

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With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the medical and healthcare fields are utilizing machine learning (ML) methodologies in numerous inventive ways. ML techniques have outstripped formerly state-of-the-art techniques in medical and healthcare practices, yielding faster and more precise outcomes. Healthcare practitioners are increasingly drawn to this technology in their initiatives relating to the Internet of Behavior (IoB). This area of research scrutinizes the rationales, approaches, and timing of human technology adoption, encompassing the domains of the Internet of Things (IoT), behavioral science, and edge analytics. The significance of ML in medical and healthcare applications based on the IoB stems from its ability to analyze and interpret copious amounts of complex data instantly, providing innovative perspectives that can enhance healthcare outcomes and boost the efficiency of IoB-based medical and healthcare procedures and thus aid in diagnoses, treatment protocols, and clinical decision making. As a result of the inadequacy of thorough inquiry into the employment of ML-based approaches in the context of using IoB for healthcare applications, we conducted a study on this subject matter, introducing a novel taxonomy that underscores the need to employ each ML method distinctively. With this objective in mind, we have classified the cutting-edge ML solutions for IoB-based healthcare challenges into five categories, which are convolutional neural networks (CNNs), recurrent neural networks (RNNs), deep neural networks (DNNs), multilayer perceptions (MLPs), and hybrid methods. In order to delve deeper, we conducted a systematic literature review (SLR) that examined critical factors, such as the primary concept, benefits, drawbacks, simulation environment, and datasets. Subsequently, we highlighted pioneering studies on ML methodologies for IoB-based medical issues. Moreover, several challenges related to the implementation of ML in healthcare and medicine have been tackled, thereby gradually fostering further research endeavors that can enhance IoB-based health and medical studies. Our findings indicated that Tensorflow was the most commonly utilized simulation setting, accounting for 24% of the proposed methodologies by researchers. Additionally, accuracy was deemed to be the most crucial parameter in the majority of the examined papers.

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A Multi-Type Transferable Method for Missing Link Prediction in Heterogeneous Social Networks

Cited by 43 publications

References 44 publications

Do network synergies facilitates the realization of M&A motivation?: From the perspective of network node degree and strength change

Do network synergies facilitates the realization of M&A motivation?: From the perspective of network node degree and strength change

Digital threads in turbulent times: unraveling technostress and cleaner production in the food industry

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors

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