Pub Date : 2020-05-08DOI: 10.1504/ijcse.2020.10029386
Yanning Cao, Xiaoshu Zhang, Jin Wang
We are in an era of digital medicine in which physicians can generate copious patient data, but tools to analyse these data are limited. Thus, we used case data from patients with oesophageal cancer from a medical institution, removed incomplete information, and quantified the textual data according to recommendations from the corresponding physicians. We used different classification algorithms to process the data, predict patient survival, and compare accuracies across algorithms. Our experimental results show that the BayesNet algorithm was highly accurate and precise, and, thus, may represent a promising data-mining tool.
{"title":"Case data-mining analysis for patients with oesophageal cancer","authors":"Yanning Cao, Xiaoshu Zhang, Jin Wang","doi":"10.1504/ijcse.2020.10029386","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029386","url":null,"abstract":"We are in an era of digital medicine in which physicians can generate copious patient data, but tools to analyse these data are limited. Thus, we used case data from patients with oesophageal cancer from a medical institution, removed incomplete information, and quantified the textual data according to recommendations from the corresponding physicians. We used different classification algorithms to process the data, predict patient survival, and compare accuracies across algorithms. Our experimental results show that the BayesNet algorithm was highly accurate and precise, and, thus, may represent a promising data-mining tool.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127690697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029212
Zhiqiang Ruan, Dan Yang
It is more popular for a multimedia service provider (MCSP) to deploy many data centres (DCs) in different geographic locations over cloud for delivering video-on-demand (VoD) services to a lot of users. One primary task of the MCSP is to maximise its profit while guarantee the user's quality-of-service (QoS) requirements. However, the stochastic arrival of user requests and the capacity restriction of individual DC make resource management in distributed cloud more challenging than in a general cloud. We present a resource assignment strategy that can accommodate heterogeneous network resources and QoS demands by converting the request distribution problem into the constrained function optimisation problem. An online algorithm is developed and certified approximating to the optimum solution. Compared with other alternatives, our algorithm can cut down more than 35% of operational cost without degrading the QoS of end users.
{"title":"Self-organised resource assignment for on-demand services in the cloud platform","authors":"Zhiqiang Ruan, Dan Yang","doi":"10.1504/ijcse.2020.10029212","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029212","url":null,"abstract":"It is more popular for a multimedia service provider (MCSP) to deploy many data centres (DCs) in different geographic locations over cloud for delivering video-on-demand (VoD) services to a lot of users. One primary task of the MCSP is to maximise its profit while guarantee the user's quality-of-service (QoS) requirements. However, the stochastic arrival of user requests and the capacity restriction of individual DC make resource management in distributed cloud more challenging than in a general cloud. We present a resource assignment strategy that can accommodate heterogeneous network resources and QoS demands by converting the request distribution problem into the constrained function optimisation problem. An online algorithm is developed and certified approximating to the optimum solution. Compared with other alternatives, our algorithm can cut down more than 35% of operational cost without degrading the QoS of end users.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129804582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029208
Mohammed Amine Benmahdjoub, A. Mezouar, L. Boumediene, Youcef Saidi
To improve the quality of life and its comfort with more security, the world of transport is moving towards the all-electric. This imposes an embarked electrical network type operation, and this network based on parallel alternators connecting, which requires more energy and needs synchronisation with identical phases between alternators. In addition, some conditions must be respected to avoid energy crises and increase the efficiency of the system. To ensure the stability and protection of this type of system, the control will be performed by a reliable controller with remote control and monitoring of all data in real time. In this paper, we realise a prototype of protection and monitoring of electrical equipment using a Raspberry Pi as an intermediate embedded system and an RPi camera. In addition, the communication between the electrical system and the web application will be done by Json file or by data stored in the database. For any change in the desired values, the electrical protection system sends a message and a musical warning to the website in real time. In addition, the monitoring will be generated by the FIFO memory for image processing and the servomotor to control the direction of the RPi camera.
{"title":"Smart embarked electrical network based on embedded system and monitoring camera","authors":"Mohammed Amine Benmahdjoub, A. Mezouar, L. Boumediene, Youcef Saidi","doi":"10.1504/ijcse.2020.10029208","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029208","url":null,"abstract":"To improve the quality of life and its comfort with more security, the world of transport is moving towards the all-electric. This imposes an embarked electrical network type operation, and this network based on parallel alternators connecting, which requires more energy and needs synchronisation with identical phases between alternators. In addition, some conditions must be respected to avoid energy crises and increase the efficiency of the system. To ensure the stability and protection of this type of system, the control will be performed by a reliable controller with remote control and monitoring of all data in real time. In this paper, we realise a prototype of protection and monitoring of electrical equipment using a Raspberry Pi as an intermediate embedded system and an RPi camera. In addition, the communication between the electrical system and the web application will be done by Json file or by data stored in the database. For any change in the desired values, the electrical protection system sends a message and a musical warning to the website in real time. In addition, the monitoring will be generated by the FIFO memory for image processing and the servomotor to control the direction of the RPi camera.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121343784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029223
Jingzhao Li, Zhi Xu
The underground coal mine monitoring system has high costs of large-scale application, the network is not easy to expand, and it is difficult to achieve complete coverage of coal mines. To solve these problems, this paper presents a new data acquisition and transmission method based on 'wired + wireless', 'A, B, C and D class mobile node'. The method, combining the existing wired network and wireless network in the coal mine, using sparse heterogeneous converged networks centred on opportunistic networks, analyses the composition, function, connection law and historical information of four types of node and the system structure. Experimental results show that this method can further realise the dynamic planning of the node interaction path. Then, it predicts and corrects the data of artificial mobile nodes and fixed interaction information in the next cycle. Finally, it achieves a powerful guarantee for internet of things, interaction of objects, intelligent perception, and intelligent processing in the mine safety management.
{"title":"Research on network layout strategy of mobile opportunity perception in coal mines","authors":"Jingzhao Li, Zhi Xu","doi":"10.1504/ijcse.2020.10029223","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029223","url":null,"abstract":"The underground coal mine monitoring system has high costs of large-scale application, the network is not easy to expand, and it is difficult to achieve complete coverage of coal mines. To solve these problems, this paper presents a new data acquisition and transmission method based on 'wired + wireless', 'A, B, C and D class mobile node'. The method, combining the existing wired network and wireless network in the coal mine, using sparse heterogeneous converged networks centred on opportunistic networks, analyses the composition, function, connection law and historical information of four types of node and the system structure. Experimental results show that this method can further realise the dynamic planning of the node interaction path. Then, it predicts and corrects the data of artificial mobile nodes and fixed interaction information in the next cycle. Finally, it achieves a powerful guarantee for internet of things, interaction of objects, intelligent perception, and intelligent processing in the mine safety management.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126453417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029225
Pei Yang, Wei Song, Xiaobing Zhao, Rui Zheng, L. Qingge
Image segmentation is widely used as a fundamental step for various image processing applications. This paper focuses on improving the famous image thresholding method named Otsu's algorithm. Based on the fact that threshold acquired by Otsu's algorithm tends to be closer to the class with larger intraclass variance when the foreground and background have large intraclass variance difference, an improved strategy is proposed to adjust the threshold bias. We analysed the relationship between pixel greyscale value and the change of cumulative pixel number, and selected the ratio of pixel grey level value to a certain cumulative pixel number as the adjusted threshold. Experiments using typical testing images were set up to verify the proposed method both quantitatively and qualitatively. Two widely used metrics named misclassification error (ME) and dice similarity coefficient (DSC) were adopted for quantitative evaluation, and both quantitative and qualitative results indicated that the proposed algorithm could better segment the testing images and get competitive misclassification error and DSC values compared with Otsu's method and its improved versions proposed by Hu and Gong (2009) and Xu et al. (2011), and the time consumption of our method can be significantly reduced.
图像分割作为各种图像处理应用的基本步骤被广泛使用。本文主要对著名的图像阈值分割方法Otsu算法进行改进。基于Otsu算法获取的阈值在前景和背景的类内方差较大时趋向于更接近类内方差较大的类别，提出了一种改进的阈值偏差调整策略。分析了像素灰度值与累积像素数变化的关系，选择像素灰度值与一定累积像素数的比值作为调整阈值。利用典型的测试图像建立了实验，从定量和定性两个方面验证了所提出的方法。采用误分误差(ME)和dice similarity coefficient (DSC)这两个被广泛使用的度量指标进行定量评价，定量和定性结果均表明，与Otsu的方法及Hu and Gong(2009)和Xu et al.(2011)提出的改进版本相比，本文算法能够更好地分割测试图像，获得有竞争力的误分类误差和DSC值，并且可以显著减少我们方法的耗时。
{"title":"An improved Otsu threshold segmentation algorithm","authors":"Pei Yang, Wei Song, Xiaobing Zhao, Rui Zheng, L. Qingge","doi":"10.1504/ijcse.2020.10029225","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029225","url":null,"abstract":"Image segmentation is widely used as a fundamental step for various image processing applications. This paper focuses on improving the famous image thresholding method named Otsu's algorithm. Based on the fact that threshold acquired by Otsu's algorithm tends to be closer to the class with larger intraclass variance when the foreground and background have large intraclass variance difference, an improved strategy is proposed to adjust the threshold bias. We analysed the relationship between pixel greyscale value and the change of cumulative pixel number, and selected the ratio of pixel grey level value to a certain cumulative pixel number as the adjusted threshold. Experiments using typical testing images were set up to verify the proposed method both quantitatively and qualitatively. Two widely used metrics named misclassification error (ME) and dice similarity coefficient (DSC) were adopted for quantitative evaluation, and both quantitative and qualitative results indicated that the proposed algorithm could better segment the testing images and get competitive misclassification error and DSC values compared with Otsu's method and its improved versions proposed by Hu and Gong (2009) and Xu et al. (2011), and the time consumption of our method can be significantly reduced.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115110789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029224
Jiang-Yi Lin, Yu Chen, Chinchen Chang, Yu-Chen Hu
In this paper, we design a novel turtle shell based data hiding scheme. The proposed scheme starts by constructing a novel reference matrix based on the original turtle shell matrix. Without any overhead messages, the secret data can be concealed in the pixel pairs selected from the cover image and would be correctly extracted according to the characteristic of the reference matrix in a 4 × 5 block. Experimental results demonstrate that the proposed scheme can achieve a high embedding capacity of 2 bit per pixel (bpp). The experimental comparison also reveals that the proposed scheme is superior to some existing data hiding schemes subject to the peak signal-to-noise ratio measurement. Meanwhile, it has good performance on resisting the statistical attack of pixel-value differencing (PVD) histogram.
{"title":"A novel high capacity turtle shell-based data hiding with location table free","authors":"Jiang-Yi Lin, Yu Chen, Chinchen Chang, Yu-Chen Hu","doi":"10.1504/ijcse.2020.10029224","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029224","url":null,"abstract":"In this paper, we design a novel turtle shell based data hiding scheme. The proposed scheme starts by constructing a novel reference matrix based on the original turtle shell matrix. Without any overhead messages, the secret data can be concealed in the pixel pairs selected from the cover image and would be correctly extracted according to the characteristic of the reference matrix in a 4 × 5 block. Experimental results demonstrate that the proposed scheme can achieve a high embedding capacity of 2 bit per pixel (bpp). The experimental comparison also reveals that the proposed scheme is superior to some existing data hiding schemes subject to the peak signal-to-noise ratio measurement. Meanwhile, it has good performance on resisting the statistical attack of pixel-value differencing (PVD) histogram.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116184162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029220
Xiufang Qian, Huamei Shi, Chunpeng Ge, H. Fan, Xiaorong Zhao, Yijun Liu
College students' innovation and entrepreneurship education is an education to cultivate college students' innovative spirit, entrepreneurial awareness and ability to improve innovation and entrepreneurship. At present, the actual development effect of innovation and entrepreneurship education in China is not obvious. The innovation ability of college students needs to be improved, the proportion of innovation and entrepreneurship is still relatively low, and the success rate of entrepreneurship is not high. Therefore, we suggest that university libraries need to make full use of big data technology to better serve innovation and entrepreneurship education, thus effectively improving the effectiveness of innovation and entrepreneurship education, and facilitating the development of more innovative and entrepreneurial talents. Firstly, it expounds the connotation of innovation and entrepreneurship education, analyses the application of big data in university libraries, and secondly proposes the mechanism of cross-functional collaboration. Then, by integrating the independent data resources of university functional departments, the mechanism overcomes the problem of 'fragmentation'; finally, and innovatively proposed the establishment of new archives, and then through the means of big data for innovation and entrepreneurship education, and ultimately improve the quality of innovation and entrepreneurship education.
{"title":"Application research on service innovation and entrepreneurship education in university libraries and archives","authors":"Xiufang Qian, Huamei Shi, Chunpeng Ge, H. Fan, Xiaorong Zhao, Yijun Liu","doi":"10.1504/ijcse.2020.10029220","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029220","url":null,"abstract":"College students' innovation and entrepreneurship education is an education to cultivate college students' innovative spirit, entrepreneurial awareness and ability to improve innovation and entrepreneurship. At present, the actual development effect of innovation and entrepreneurship education in China is not obvious. The innovation ability of college students needs to be improved, the proportion of innovation and entrepreneurship is still relatively low, and the success rate of entrepreneurship is not high. Therefore, we suggest that university libraries need to make full use of big data technology to better serve innovation and entrepreneurship education, thus effectively improving the effectiveness of innovation and entrepreneurship education, and facilitating the development of more innovative and entrepreneurial talents. Firstly, it expounds the connotation of innovation and entrepreneurship education, analyses the application of big data in university libraries, and secondly proposes the mechanism of cross-functional collaboration. Then, by integrating the independent data resources of university functional departments, the mechanism overcomes the problem of 'fragmentation'; finally, and innovatively proposed the establishment of new archives, and then through the means of big data for innovation and entrepreneurship education, and ultimately improve the quality of innovation and entrepreneurship education.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122049856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029211
R. Achar, P. S. Thilagam, Shreenath Acharya
Cloud computing has recently emerged as a new computing paradigm for delivering on demand virtualised computing resources over the internet on a pay-as-use basis. Applications hosted in cloud have different requirements which include both low level (resource) requirements and high level (performance) requirements. However, most of the cloud providers satisfy SLAs based on resource requirements rather than providing performance guarantees to applications. This gap creates a need for selecting a more suitable cloud provider who can satisfy performance requirements of applications along with resource requirements. This work aims at proposing a broker-based approach to rank cloud providers based on QoS requirements of customers. It helps the SaaS providers to save cost and complexity in choosing a suitable cloud provider for hosting applications. The experimental results show that proposed approach selects the suitable cloud provider for hosting various types of applications satisfying the needs of different cloud customers.
{"title":"Broker-based mechanism for cloud provider selection","authors":"R. Achar, P. S. Thilagam, Shreenath Acharya","doi":"10.1504/ijcse.2020.10029211","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029211","url":null,"abstract":"Cloud computing has recently emerged as a new computing paradigm for delivering on demand virtualised computing resources over the internet on a pay-as-use basis. Applications hosted in cloud have different requirements which include both low level (resource) requirements and high level (performance) requirements. However, most of the cloud providers satisfy SLAs based on resource requirements rather than providing performance guarantees to applications. This gap creates a need for selecting a more suitable cloud provider who can satisfy performance requirements of applications along with resource requirements. This work aims at proposing a broker-based approach to rank cloud providers based on QoS requirements of customers. It helps the SaaS providers to save cost and complexity in choosing a suitable cloud provider for hosting applications. The experimental results show that proposed approach selects the suitable cloud provider for hosting various types of applications satisfying the needs of different cloud customers.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126039039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029209
Wei Fang, Tianxiao Jiang, Ke Jiang, Feihong Zhang, Yewen Ding, Jack Sheng
Deep learning is currently developing very fast in the NLP field and has achieved many amazing results in the past few years. Automatic text summarisation means that the abstract of the document is automatically summarised by a computer program without changing the original intention of the document. There are many application scenarios for automatic summarisation, such as news headline generation, scientific document abstract generation, search result segment generation, and product review summarisation. In the era of internet big data in the information explosion, if the short text can be employed to express the main connotation of information, it will undoubtedly help to alleviate the problem of information overload. In this paper, a model based on the long short-term memory network is presented to automatically analyse and summarise Chinese articles by using the seq2seq+attention models. Finally, the experimental results are attached and evaluated.
{"title":"A method of automatic text summarisation based on long short-term memory","authors":"Wei Fang, Tianxiao Jiang, Ke Jiang, Feihong Zhang, Yewen Ding, Jack Sheng","doi":"10.1504/ijcse.2020.10029209","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029209","url":null,"abstract":"Deep learning is currently developing very fast in the NLP field and has achieved many amazing results in the past few years. Automatic text summarisation means that the abstract of the document is automatically summarised by a computer program without changing the original intention of the document. There are many application scenarios for automatic summarisation, such as news headline generation, scientific document abstract generation, search result segment generation, and product review summarisation. In the era of internet big data in the information explosion, if the short text can be employed to express the main connotation of information, it will undoubtedly help to alleviate the problem of information overload. In this paper, a model based on the long short-term memory network is presented to automatically analyse and summarise Chinese articles by using the seq2seq+attention models. Finally, the experimental results are attached and evaluated.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122488473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-04DOI: 10.1504/ijcse.2020.10029215
Yan Yuan, Bolun Chen, Yongtao Yu, Ying Jin
Influence maximisation is an important research direction in social networks. The main goal of this approach is to select seed nodes in the network to maximise the propagated influence. Because the influence maximisation is an NP-hard problem, existing studies have provided approximate solutions, and the research focuses on the framework of greed, but the time complexity of the greedy algorithm is high. In this study, an influence maximisation algorithm based on community detection is proposed. This algorithm uses the K-means algorithm to divide the community. According to the modularity, the optimal community segmentation result is selected. By calculating the edge betweenness of each community, some nodes are selected as important nodes. The important nodes of each community constitute the set of seed nodes used in the influence maximisation algorithm. Experiments show that the algorithm not only has an improved influence, but also the time complexity is effectively reduced.
{"title":"An influence maximisation algorithm based on community detection","authors":"Yan Yuan, Bolun Chen, Yongtao Yu, Ying Jin","doi":"10.1504/ijcse.2020.10029215","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10029215","url":null,"abstract":"Influence maximisation is an important research direction in social networks. The main goal of this approach is to select seed nodes in the network to maximise the propagated influence. Because the influence maximisation is an NP-hard problem, existing studies have provided approximate solutions, and the research focuses on the framework of greed, but the time complexity of the greedy algorithm is high. In this study, an influence maximisation algorithm based on community detection is proposed. This algorithm uses the K-means algorithm to divide the community. According to the modularity, the optimal community segmentation result is selected. By calculating the edge betweenness of each community, some nodes are selected as important nodes. The important nodes of each community constitute the set of seed nodes used in the influence maximisation algorithm. Experiments show that the algorithm not only has an improved influence, but also the time complexity is effectively reduced.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122674468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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