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Open Access
Article
Publication date: 4 September 2017

Yuqin Wang, Bing Liang, Wen Ji, Shiwei Wang and Yiqiang Chen

In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors…

2455

Abstract

Purpose

In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors, and learners all over the world can get access to these courses via the internet. However, faced with massive courses, learners often waste much time finding courses they like. This paper aims to explore the problem that how to make accurate personalized recommendations for MOOC users.

Design/methodology/approach

This paper proposes a multi-attribute weight algorithm based on collaborative filtering (CF) to select a recommendation set of courses for target MOOC users.

Findings

The recall of the proposed algorithm in this paper is higher than both the traditional CF and a CF-based algorithm – uncertain neighbors’ collaborative filtering recommendation algorithm. The higher the recall is, the more accurate the recommendation result is.

Originality/value

This paper reflects the target users’ preferences for the first time by calculating separately the weight of the attributes and the weight of attribute values of the courses.

Details

International Journal of Crowd Science, vol. 1 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 16 October 2018

Jing Liu, Zhiwen Pan, Jingce Xu, Bing Liang, Yiqiang Chen and Wen Ji

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a…

1239

Abstract

Purpose

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.

Design/methodology/approach

This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.

Findings

By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.

Originality/value

This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

Details

International Journal of Crowd Science, vol. 2 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 3 June 2021

Lulu Ge, Zheming Yang and Wen Ji

The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to…

Abstract

Purpose

The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to complete tasks through the cooperation of many agents. In this study, the evolution of crowd intelligence is studied through the clustering method and the particle swarm optimization (PSO) algorithm.

Design/methodology/approach

This study proposes a crowd evolution method based on intelligence level clustering. Based on clustering, this method uses the agents’ intelligence level as the metric to cluster agents. Then, the agents evolve within the cluster on the basis of the PSO algorithm.

Findings

Two main simulation experiments are designed for the proposed method. First, agents are classified based on their intelligence level. Then, when evolving the agents, two different evolution centers are set. Besides, this paper uses different numbers of clusters to conduct experiments.

Practical implications

The experimental results show that the proposed method can effectively improve the crowd intelligence level and the cooperation ability between agents.

Originality/value

This paper proposes a crowd evolution method based on intelligence level clustering, which is based on the clustering method and the PSO algorithm to analyze the evolution.

Details

International Journal of Crowd Science, vol. 5 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 3 June 2021

Ke Wang, Zheming Yang, Bing Liang and Wen Ji

The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in…

Abstract

Purpose

The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently.

Design/methodology/approach

In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices.

Findings

Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level.

Originality/value

This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.

Details

International Journal of Crowd Science, vol. 5 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 9 July 2021

Jianran Liu, Bing Liang and Wen Ji

Artificial intelligence is gradually penetrating into human society. In the network era, the interaction between human and artificial intelligence, even between artificial…

Abstract

Purpose

Artificial intelligence is gradually penetrating into human society. In the network era, the interaction between human and artificial intelligence, even between artificial intelligence, becomes more and more complex. Therefore, it is necessary to describe and intervene the evolution of crowd intelligence network dynamically. This paper aims to detect the abnormal agents at the early stage of intelligent evolution.

Design/methodology/approach

In this paper, differential evolution (DE) and K-means clustering are used to detect the crowd intelligence with abnormal evolutionary trend.

Findings

This study abstracts the evolution process of crowd intelligence into the solution process of DE and use K-means clustering to identify individuals who are not conducive to evolution in the early stage of intelligent evolution.

Practical implications

Experiments show that the method we proposed are able to find out individual intelligence without evolutionary trend as early as possible, even in the complex crowd intelligent interactive environment of practical application. As a result, it can avoid the waste of time and computing resources.

Originality/value

In this paper, DE and K-means clustering are combined to analyze the evolution of crowd intelligent interaction.

Details

International Journal of Crowd Science, vol. 5 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Article
Publication date: 1 August 2016

Ji Wen, Yina Li and Pingping Hou

This study mainly aims to examine the mediating effect of perceived organizational support (POS) and the moderating effect of locus of control and job autonomy on the relationship…

3447

Abstract

Purpose

This study mainly aims to examine the mediating effect of perceived organizational support (POS) and the moderating effect of locus of control and job autonomy on the relationship between customer mistreatment behavior and organizational citizenship behavior.

Design/methodology/approach

Through a questionnaire survey of 231 employees and their direct supervisors of five hotels in Guangzhou. This paper analyzed five variables (customer mistreatment, POS, locus of control, job autonomy and organizational citizenship behavior) relationships through a variety of data analysis.

Findings

Results indicate that customer mistreatment behavior has a negative effect on employees’ organizational citizenship behavior. The relationship between customer mistreatment behavior and employees’ organizational citizenship behavior is partially mediated by employees’ POS. Staffs’ locus of control and job autonomy can modulate the relationship between customers’ mistreatment behavior and POS. Furthermore, the indirect mediating effect of POS on customer mistreatment behavior is revealed. The organizational citizenship behavior linkage is significant only to staff who perceived they have a high level of job autonomy and a high locus of control.

Practical implications

Hotels are advised to provide organizational support and the management of customer mistreatment behavior so as to reflect their employees’ value, seek service innovation and promote production efficiency in practice. Furthermore, it maintains and promotes operational efficiency for service organizations and means the organization pays more attention to meet the social, emotional and psychological needs of its employees.

Originality/value

This article reveals the mechanism relationship between customer mistreatment behavior and employee organizational citizenship behavior. First, it defines the concept of customer mistreatment in the hotel industry and enriches the related research. Second, the study, from the perspective of customer mistreatment, has opened up a new view of organizational citizenship behavior research. Third, we built a research model and it is helpful to grasp the inner mechanism between customer mistreatment and employees’ organizational citizenship behavior. Fourth, this research benefits service organizations so as to maintain and improve their operation efficiency. Furthermore, it can have theoretical guidance for service-oriented organizations to develop a harmonious consumption culture and organizational culture.

Details

Nankai Business Review International, vol. 7 no. 3
Type: Research Article
ISSN: 2040-8749

Keywords

Article
Publication date: 19 March 2018

Ji Wen, Yaou Hu and Hyun Jeong Kim

The purpose of this study is to extend cognitive appraisal theory by integrating customers’ individual difference factors, specifically cultural values. This study examines the…

3196

Abstract

Purpose

The purpose of this study is to extend cognitive appraisal theory by integrating customers’ individual difference factors, specifically cultural values. This study examines the effect of individual cultural values on hotel customers’ positive emotions and electronic word-of-mouth (eWOM) creation intention.

Design/methodology/approach

Online surveys were administered via MTurk. Adults with a recent hotel stay were invited to participate in this study. In all, 331 valid questionnaires were used for data analysis.

Findings

The results show that collectivism, indulgence and power distance have positive effects on pride, and that indulgence has a positive effect on pleasure. Both pleasure and pride have significant impacts on eWOM creation intention, with the effect of pleasure being stronger.

Practical implications

This study deepens hotel practitioners’ understanding of the formation of hotel guests’ eWOM creation intention and offers suggestions on how to facilitate eWOM advocacy.

Originality/value

This study highlights the versatility of cognitive appraisal theory with the inclusion of individual cultural values in the hotel eWOM context. This study delineates the underlying psychological process of how individual cultural values lead to positive eWOM intention via positive emotions that hotel guests experience during their visit. This psychological process is understudied, yet critical for the success of hotel companies that cater to many culturally diverse guests.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Open Access
Article
Publication date: 2 July 2020

Zheming Yang and Wen Ji

The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The…

Abstract

Purpose

The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The different agent is generally difficult to measure because of the uncertainty between multiple factors. The purpose of this paper is to solve the problem of uncertainty between multiple factors and propose an effective method for universal intelligence measurement for the different agents.

Design/methodology/approach

In this paper, the authors propose a universal intelligence measurement method based on meta-analysis for crowd network. First, the authors get study data through keywords in the database and delete the low-quality data. Second, they compute the effect value by odds ratio, relative risk and risk difference. Then, they test the homogeneity by Q-test and analyze the bias by funnel plots. Third, they select the fixed effect and random effect as a statistical model. Finally, through the meta-analysis of time, complexity and reward, the weight of each factor in the intelligence measurement is obtained and then the meta measurement model is constructed.

Findings

This paper studies the relationship among time, complexity and reward through meta-analysis and effectively combines the measurement of heterogeneous agents such as human, machine, enterprise, government and institution.

Originality/value

This paper provides a universal intelligence measurement model for crowd network. And it can provide a theoretical basis for the research of crowd science.

Details

International Journal of Crowd Science, vol. 4 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 7 October 2021

Jianran Liu and Wen Ji

In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network…

Abstract

Purpose

In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network has become increasingly complex. Therefore, it is necessary to model and analyze this complex interactive network. This paper aims to model and demonstrate the evolution of crowd intelligence using visual complex networks.

Design/methodology/approach

This paper uses the complex network to model and observe the collaborative evolution behavior and self-organizing system of crowd intelligence.

Findings

The authors use the complex network to construct the cooperative behavior and self-organizing system in crowd intelligence. Determine the evolution mode of the node by constructing the interactive relationship between nodes and observe the global evolution state through the force layout.

Practical implications

The simulation results show that the state evolution map can effectively simulate the distribution, interaction and evolution of crowd intelligence through force layout and the intelligent agents’ link mode the authors proposed.

Originality/value

Based on the complex network, this paper constructs the interactive behavior and organization system in crowd intelligence and visualizes the evolution process.

Details

International Journal of Crowd Science, vol. 5 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 5 August 2021

Rui Qiu and Wen Ji

Many recommender systems are generally unable to provide accurate recommendations to users with limited interaction history, which is known as the cold-start problem. This issue…

Abstract

Purpose

Many recommender systems are generally unable to provide accurate recommendations to users with limited interaction history, which is known as the cold-start problem. This issue can be resolved by trivial approaches that select random items or the most popular one to recommend to the new users. However, these methods perform poorly in many cases. This paper aims to explore the problem that how to make accurate recommendations for the new users in cold-start scenarios.

Design/methodology/approach

In this paper, the authors propose embedded-bandit method, inspired by Word2Vec technique and contextual bandit algorithm. The authors describe user contextual information with item embedding features constructed by Word2Vec. In addition, based on the intelligence measurement model in Crowd Science, the authors propose a new evaluation method to measure the utility of recommendations.

Findings

The authors introduce Word2Vec technique for constructing user contextual features, which improved the accuracy of recommendations compared to traditional multi-armed bandit problem. Apart from this, using this study’s intelligence measurement model, the utility also outperforms.

Practical implications

Improving the accuracy of recommendations during the cold-start phase can greatly raise user stickiness and increase user favorability, which in turn contributes to the commercialization of the app.

Originality/value

The algorithm proposed in this paper reflects that user contextual features can be represented by clicked items embedding vector.

Details

International Journal of Crowd Science, vol. 5 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

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