An Improved Evaluation Methodology for Mining Association Rules

Bao, Fuguang; Mao, Linghao; Zhu, Yiling; Xiao, Cancan; Xu, Chonghuan

doi:10.3390/axioms11010017

Cited by 31 publications

(12 citation statements)

References 41 publications

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“…It optimizes the measurement of connection tightness of network structure and adds the calculation of asymmetric interaction intensity and the matching degree of personality link preference to the social relationship prediction model, which improves the model’s accuracy. In the future, research results can be applied to various fields, including personalized recommendation ( Xu et al, 2020 , 2021a , b ; Bao et al, 2022 ), sustainable tourism ( Xiang et al, 2021 ; Wang et al, 2022 ), personal health ( Tang Z. et al, 2021 ), and so on.…”

Section: Discussionmentioning

confidence: 99%

“… Mo et al (2022) proposed a deep learning framework for temporal network link prediction. Bao et al (2022) proposed an improved evaluation methodology for association rules and link prediction. Wei et al (2022) proposed a novel time series-based graph model with text, called text with time series for graph (TT-Graph) model, which explicitly considers the user similarity and time series similarity.…”

Section: Related Workmentioning

confidence: 99%

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Social Relationship Prediction Integrating Personality Traits and Asymmetric Interactions

Bao

et al. 2022

Front. Psychol.

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Social networks have become an important way for users to find friends and expand their social circle. Social networks can improve users’ experience by recommending more suitable friends to them. The key lies in improving the accuracy of link prediction, which is also the main research issue of this study. In the study of personality traits, some scholars have proved that personality can be used to predict users’ behavior in social networks. Based on these studies, this study aims to improve the accuracy of link prediction in directed social networks. Considering the integration of personality link preference and asymmetric interaction into the link prediction model of social networks, a four-dimensional link prediction model is proposed. Through comparative experiments, it is proved that the four-dimensional social relationship prediction model proposed in this study is more accurate than the model only based on similarity. At the same time, it is also verified that the matching degree of personality link preference and asymmetric interaction intensity in the model can help improve the accuracy of link prediction.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Social Relationship Prediction Integrating Personality Traits and Asymmetric Interactions

Bao

et al. 2022

Front. Psychol.

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“…From the perspective of research innovation ( 35 – 38 ), countries with strong innovation in carbon neutrality research are the United States, Australia, Germany, Japan, France, and other developed countries, and one institution with strong innovation is Univ Toronto (Canada). It is found that these countries and institutions lead the development of global carbon neutrality.…”

Section: Discussionmentioning

confidence: 99%

Visualization and Bibliometric Analysis of Carbon Neutrality Research for Global Health

Mao

Zhu

et al. 2022

Front. Public Health

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The visual analysis of carbon neutrality research can help better understand the development of the research field and explore the difficulties and hot spots in the research, thus making contributions to “carbon emission reduction,” environmental protection and human health. This paper makes a visual quantitative analysis of 2,819 research papers published in top international journals from 2008 to 2021 in the WOS core database. It is found that China, the United States, Britain, and Germany are leading the way in carbon neutrality research. The research hotspots are mainly divided into three dimensions: (1) biomass energy and the negative effects it might bring; (2) ways and methods of electrochemical reduction of carbon dioxide; (3) catalysts and catalytic environment. The research mainly went through the conceptual period of 1997–2007, the exploration period of bioenergy from 2008 to 2021, the criticized period of bioenergy sources from 2011 to 2013, and the carbon dioxide electroreduction period from 2013 to the present. In the future, the research direction of biomass energy is to find one kind of biomass energy source which can be stored in a low-carbon way, produced in large quantities at a low cost, and will not occupy forestland. The electrolysis of water to produce hydrogen and the synthesis of fuel with CO2 are two major research directions at present, whose aims are to find the suitable catalyst and environment for the reaction. Besides, more research can be done on “carbon neutrality” policies so as to reduce carbon dioxide emissions from the source, develop a low-carbon economy and protect human health.

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“…This phenomenon makes the data tracing pressure of the full node surge in the sales season, which we call the consumer-level-traceability request pressure. Instead of focusing on professional data, consumers pay more attention to visual data such as images and videos with a strong presentation [15][16][17]. This paper aims to solve the pressure of consumer-level traceability and meet the needs of consumers, using the image evidence as a means of enhancement to build a consumer-level-traceability system based on blockchain technology.…”

Section: Introductionmentioning

confidence: 99%

Blockchain Traceability System in Complex Application Scenarios: Image-Based Interactive Traceability Structure

Shen

Bao

et al. 2022

Systems

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To solve the problems exposed by the application of blockchain technology under complex scenarios, such as fraudulent use of data, hard to store huge amounts of data, and low traceability efficiency under an ultra-huge number of traceability requests, this paper constructs an image-based interactive traceability structure by using images as an enhancement. By adding pointers to raw image files, a specific file structure is formed for traceability, and the traceability process is separated from the verification process, therefore realizing the distributed traceability of “traceability off the chain and verification on the chain”. The experimental results show that, compared with the traditional blockchain traceability mode, the interactive traceability structure can reduce the data retrieval pressure and greatly improve the traceability efficiency of a specific transaction chain. With the growth of the span of the transaction chain, the traceability efficiency advantage of the interactive traceability structure becomes more obvious.

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An Improved Evaluation Methodology for Mining Association Rules

Cited by 31 publications

References 41 publications

Social Relationship Prediction Integrating Personality Traits and Asymmetric Interactions

Social Relationship Prediction Integrating Personality Traits and Asymmetric Interactions

Visualization and Bibliometric Analysis of Carbon Neutrality Research for Global Health

Blockchain Traceability System in Complex Application Scenarios: Image-Based Interactive Traceability Structure

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