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Article
Publication date: 27 November 2020

Mingwei Tang, Jiangping Chen, Haihua Chen, Zhenyuan Xu, Yueyao Wang, Mengting Xie and Jiangwei Lin

The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a digital…

364

Abstract

Purpose

The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a digital collection is established or curated. It aims to create a retrieval approach which could return the results by meanings rather than by keywords.

Design/methodology/approach

In this paper, the authors propose a semantic term frequency algorithm to create a semantic vector space model (SeVSM) based on ontology. To support the calculation, a multi-branches tree model is created to represent the ontology and a set of algorithms is developed to operate it. Then, a semantic ontology-based IR system based on the SeVSM model is designed and developed to verify the effectiveness of the proposed model.

Findings

The experimental study using 30 queries from 15 different domains confirms the effectiveness of the SeVSM and the usability of the proposed system. The results demonstrate that the proposed model and system can be a significant exploration to enhance IR in specific domains, such as a digital library and e-commerce.

Originality/value

This research not only creates a semantic retrieval model, but also provides the application approach via designing and developing a semantic retrieval system based on the model. Comparing with most of the current related research, the proposed research studies the whole process of realizing a semantic retrieval.

Details

The Electronic Library , vol. 38 no. 5/6
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 13 June 2024

Jiaojiao Qu, Mingwei Liu, Shuming Zhao, Yixuan Zhao and Xia Cao

The function of cognitive diversity has not yet been studied to a sufficient degree. To address this gap, the current study aims to answer the questions of how and when team…

269

Abstract

Purpose

The function of cognitive diversity has not yet been studied to a sufficient degree. To address this gap, the current study aims to answer the questions of how and when team cognitive diversity fosters individual creativity by integrating the intellectual capital view and the inclusion literature.

Design/methodology/approach

With a paired and time-lagged sample consisting of 368 members and 46 leaders from Chinese high-tech organizations, a multilevel moderated mediation model was developed to test the hypothesized relationships using structural equation modeling.

Findings

Team cognitive diversity is positively related to individual creativity via team intellectual capital, but this positive indirect effect is obtained only when the inclusive team climate is high.

Research limitations/implications

Team intellectual capital serves as an alternative mechanism for translating team cognitive diversity into favorable outcomes, and an inclusive team climate plays a pivotal role in harvesting the benefits of team cognitive diversity. Future research could extend our study by adopting a multiwave longitudinal or experimental design, examining the possibility of curvilinearity, considering the changes in patterns over time, and conducting cross-cultural studies.

Practical implications

Managers should take the initiative to assemble a team featuring cognitive diversity when facing creative tasks, and should proactively cultivate an inclusive culture when leading such a team.

Originality/value

This study is among the first to consider the mediating role of team intellectual capital in the cross-level effect of team cognitive diversity on individual creativity and to examine the boundary role of an inclusive team climate with respect to this indirect effect.

Details

Personnel Review, vol. 53 no. 8
Type: Research Article
ISSN: 0048-3486

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Article
Publication date: 15 February 2023

Lili Zhang, Jie Ling and Mingwei Lin

The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends…

241

Abstract

Purpose

The aim of this paper is to present a comprehensive analysis of risk management in East Asia from 1998 to 2021 by using bibliometric methods and tools to explore research trends, hotspots, and directions for future research.

Design/methodology/approach

The data source for this paper is the Web of Science Core Collection, and 7,154 publications and related information have been derived. We use recognized bibliometric indicators to evaluate publications and visually analyze them through scientific mapping tools (VOS Viewer and CiteSpace).

Findings

The analysis results show that China is the most productive and influential country/region. East Asia countries have strong cooperation with each other and also have cooperation with other countries. The study shows that risk management has been involved in various fields such as credit, supply chain, health emergency and disaster especially in the background of COVID-19. We also found that machine learning, especially deep learning, has been playing an increasingly important role in risk management due to its excellent performance.

Originality/value

This paper focuses on studying risk management in East Asia, exploring its publication's fundamental information, citation and cooperation networks, hotspots, and research trends. It provides some reference value for scholars who are interested or further research in this field.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 16 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

Available. Content available
Article
Publication date: 3 September 2021

Shuming Zhao, Mingwei Liu and Meng Xi

718

Abstract

Details

Chinese Management Studies, vol. 15 no. 4
Type: Research Article
ISSN: 1750-614X

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Article
Publication date: 6 July 2020

Yi-Hsin Lin, Yanzhe Guo, Chan-Joong Kim, Po-Han Chen and Mingwei Qian

In the process of undertaking overseas construction projects, relational governance has become indispensable for project stakeholders. This study examines how relational…

344

Abstract

Purpose

In the process of undertaking overseas construction projects, relational governance has become indispensable for project stakeholders. This study examines how relational governance influences contractors' adaptability to foreign situations and whether such associations are positively moderated by international environmental complexity.

Design/methodology/approach

A crosssectional survey methodology was applied to collect primary data through questionnaires sent to domestic contractors in China and South Korea (hereafter Korea). Multiple regression analysis was used to test the effects of four dimensions of relational governance on contractor adaptability. Thereafter, the Chinese and Korean subsamples were tested separately through moderated regression analysis to explore differences in the influence of relational governance on adaptability.

Findings

The results showed that quality communication, favor exchange and establishing an emotional relationship significantly and positively affected a contractor’s adaptability. However, there were significant differences between the Chinese and Korean international contractors in terms of the moderating effects of international environment complexity.

Research limitations/implications

East Asian engagement in international development is not limited to China and Korea alone, and the study should be replicated using large representative samples from more countries, such as Japan, to gain a fuller understanding of the influence of relational governance.

Originality/value

The results have great significance for the managers of international contractors in East Asian countries and contribute to the research on relational governance and contractor adaptability.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 10
Type: Research Article
ISSN: 0969-9988

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Book part
Publication date: 10 July 2019

Jingjing Wang, Zhiqiang Li, Huanhuan Feng, Yuanjing Guo, Zhengbo Liang, Luyao Wang, Xing Wan and Yalin Wang

Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in…

Abstract

Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in knowledge sharing area, and knowledge payment is one of the most effective ways to achieve it. Therefore, the knowledge payment has been regarded as a huge business opportunity, and it is of great meaning to study the development trend and feasibility of knowledge payment. This chapter, through big data methods, analyzes the business model of Zhihu (a Chinese platform of knowledge sharing) after it introduced knowledge payment projects, such as Zhihu Live and Pay Consultation. According to data of Zhihu users’ Q&A, concerned fields and others, this chapter tries to outline its user profile to find out the target groups of different topics, the proper form of knowledge payment and the hot topics of Zhihu Live. Through the analysis of knowledge graph, this chapter finds that Zhihu Live is expected to be the mainstream knowledge payment form in the future, and the most potential topics are mainly focused on science, law, and business. Meanwhile, it establishes a pricing model for Zhihu Live, and provides suggestions for the development of knowledge payment.

Details

The New Silk Road Leads through the Arab Peninsula: Mastering Global Business and Innovation
Type: Book
ISBN: 978-1-78756-680-4

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Article
Publication date: 23 December 2024

Jiaqi Liu, Jialong Jiang, Mingwei Lin, Hong Chen and Zeshui Xu

When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are…

14

Abstract

Purpose

When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are difficult to achieve a balance between rating prediction accuracy and complexity. Therefore, the purpose of this paper is to propose an accurate and effective model to predict users’ ratings of products for the accurate recommendation of products to users.

Design/methodology/approach

First, we introduce an attention mechanism that dynamically assigns weights to user preferences, highlighting key interaction information and enhancing the model’s understanding of user behavior. Second, a fold embedding strategy is employed to segment user interaction data, increasing the information density of each subset while reducing the complexity of the attention mechanism. Finally, a masking strategy is integrated to mitigate overfitting by concealing portions of user-item interactions, thereby improving the model’s generalization ability.

Findings

The experimental results demonstrate that the proposed model significantly minimizes prediction error across five real-world datasets. On average, the evaluation metrics root mean square error (RMSE) and mean absolute error (MAE) are reduced by 9.11 and 13.3%, respectively. Additionally, the Friedman test results confirm that these improvements are statistically significant. Consequently, the proposed model more accurately captures the intrinsic correlation between users and products, leading to a substantial reduction in prediction error.

Originality/value

We propose a novel collaborative filtering model to learn the user-item interaction matrix effectively. Additionally, we introduce a fold embedding strategy to reduce the computational resource consumption of the attention mechanism. Finally, we implement a masking strategy to encourage the model to focus on key features and patterns, thereby mitigating overfitting.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 27 November 2020

Mingwei Lin, Yanqiu Chen and Riqing Chen

The purpose of this paper is to make a comprehensive analysis of 354 publications about Pythagorean fuzzy sets (PFSs) from 2013 to 2020 in order to comprehensively understand…

259

Abstract

Purpose

The purpose of this paper is to make a comprehensive analysis of 354 publications about Pythagorean fuzzy sets (PFSs) from 2013 to 2020 in order to comprehensively understand their historical progress and current situation, as well as future development trend.

Design/methodology/approach

First, this paper describes the fundamental information of these publications on PFSs, including their data information, annual trend and prediction and basic features. Second, the most productive and influential authors, countries/regions, institutions and the most cited documents are presented in the form of evaluation indicators. Third, with the help of VOSviewer software, the visualization analysis is conducted to show the development status of PFSs publications at the level of authors, countries/regions, institutions and keywords. Finally, the burst detection of keywords, timezone review and timeline review are exported from CiteSpace software to analyze the hotspots and development trend on PFSs.

Findings

The annual PFSs publications present a quickly increasing trend. The most productive author is Wei Guiwu (China). Wei Guiwu and Wei Cun have the strongest cooperative relationship.

Research limitations/implications

The implication of this study is to provide a comprehensive perspective for the scholars who take a fancy to PFSs, and it is valuable for scholars to grasp the hotspots in this field in time.

Originality/value

It is the first paper that uses the bibliometric analysis to comprehensively analyze the publications on PFSs. It can help the scholars in the field of PFSs to quickly understand the development status and trend of PFSs.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 14 no. 2
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 26 April 2022

Jianpeng Zhang and Mingwei Lin

The purpose of this paper is to make an overview of 6,618 publications of Apache Hadoop from 2008 to 2020 in order to provide a conclusive and comprehensive analysis for…

277

Abstract

Purpose

The purpose of this paper is to make an overview of 6,618 publications of Apache Hadoop from 2008 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of Apache Hadoop for interested researchers.

Design/methodology/approach

This paper employs the bibliometric analysis and visual analysis approaches to systematically study and analyze publications about Apache Hadoop in the Web of Science database. This study aims to investigate the topic of Apache Hadoop by means of bibliometric analysis with the aid of visualization applications. Through the bibliometric analysis of the collected documents, this paper analyzes the main statistical characteristics and cooperation networks. Research themes, research hotspots and future development trends are also investigated through the keyword analysis.

Findings

The research on Apache Hadoop is still the top priority in the future, and how to improve the performance of Apache Hadoop in the era of big data is one of the research hotspots.

Research limitations/implications

This paper makes a comprehensive analysis of Apache Hadoop with methods of bibliometrics, and it is valuable for researchers can quickly grasp the hot topics in this area.

Originality/value

This paper draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to understand the development status and trends in this field and inspire new ideas for researchers.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 16 no. 1
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 9 September 2024

Weixing Wang, Yixia Chen and Mingwei Lin

Based on the strong feature representation ability of the convolutional neural network (CNN), generous object detection methods in remote sensing (RS) have been proposed one after…

25

Abstract

Purpose

Based on the strong feature representation ability of the convolutional neural network (CNN), generous object detection methods in remote sensing (RS) have been proposed one after another. However, due to the large variation in scale and the omission of relevant relationships between objects, there are still great challenges for object detection in RS. Most object detection methods fail to take the difficulties of detecting small and medium-sized objects and global context into account. Moreover, inference time and lightness are also major pain points in the field of RS.

Design/methodology/approach

To alleviate the aforementioned problems, this study proposes a novel method for object detection in RS, which is called lightweight object detection with a multi-receptive field and long-range dependency in RS images (MFLD). The multi-receptive field extraction (MRFE) and long-range dependency information extraction (LDIE) modules are put forward.

Findings

To concentrate on the variability of objects in RS, MRFE effectively expands the receptive field by a combination of atrous separable convolutions with different dilated rates. Considering the shortcomings of CNN in extracting global information, LDIE is designed to capture the relationships between objects. Extensive experiments over public datasets in RS images demonstrate that our MFLD method surpasses the state-of-the-art methods. Most of all, on the NWPU VHR-10 dataset, our MFLD method achieves 94.6% mean average precision with 4.08 M model volume.

Originality/value

This paper proposed a method called lightweight object detection with multi-receptive field and long-range dependency in RS images.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 17 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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