Pub Date : 2021-03-03DOI: 10.1504/IJCSE.2021.113636
Ive Andresson Dos Santos Tourinho, T. N. Rios
Several online social networks collect information from their users' interactions (co-tagging of photos, co-rating of products, etc.) producing a large amount of activity-based data. As a consequence, this kind of information is used by these social networks to provide their users with recommendations about new products or friends. Moreover, recommendation systems (RS) become capable to predict a person's activity with no special infrastructure or hardware, such as RFID tags, or by using video and audio. In that sense, we propose a technique to provide personalised points-of-interest (POIs) recommendations for users of location-based social networks (LBSNs). Our technique assumes users' preferences can be characterised by their visited locations, which is shared by them on LBSN, collaboratively exposing important features as, for instance, areas-of-interest (AOIs) and POIs popularity. Therefore, our technique, named fuzzy areas-based collaborative filtering, uses users' activities to model their preferences and recommend the next visits to them. We have performed experiments over two real LBSN datasets and the obtained results have shown our technique outperforms location collaborative filtering at almost all of the experimental evaluation. Therefore, by fuzzy clustering of AOIs, FACF is suitable to check the popularity of POIs to improve POIs recommendation.
{"title":"FACF: fuzzy areas-based collaborative filtering for point-of-interest recommendation","authors":"Ive Andresson Dos Santos Tourinho, T. N. Rios","doi":"10.1504/IJCSE.2021.113636","DOIUrl":"https://doi.org/10.1504/IJCSE.2021.113636","url":null,"abstract":"Several online social networks collect information from their users' interactions (co-tagging of photos, co-rating of products, etc.) producing a large amount of activity-based data. As a consequence, this kind of information is used by these social networks to provide their users with recommendations about new products or friends. Moreover, recommendation systems (RS) become capable to predict a person's activity with no special infrastructure or hardware, such as RFID tags, or by using video and audio. In that sense, we propose a technique to provide personalised points-of-interest (POIs) recommendations for users of location-based social networks (LBSNs). Our technique assumes users' preferences can be characterised by their visited locations, which is shared by them on LBSN, collaboratively exposing important features as, for instance, areas-of-interest (AOIs) and POIs popularity. Therefore, our technique, named fuzzy areas-based collaborative filtering, uses users' activities to model their preferences and recommend the next visits to them. We have performed experiments over two real LBSN datasets and the obtained results have shown our technique outperforms location collaborative filtering at almost all of the experimental evaluation. Therefore, by fuzzy clustering of AOIs, FACF is suitable to check the popularity of POIs to improve POIs recommendation.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121532580","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 : 2021-01-01DOI: 10.1504/ijcse.2021.10043714
J. Vijayalakshmi, A. Murugan
{"title":"Constructive system for double-spend data detection and prevention in inter and intra-block of blockchain","authors":"J. Vijayalakshmi, A. Murugan","doi":"10.1504/ijcse.2021.10043714","DOIUrl":"https://doi.org/10.1504/ijcse.2021.10043714","url":null,"abstract":"","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121029951","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 : 2020-09-22DOI: 10.1504/IJCSE.2020.110189
Yuan Chen, Dongmei Han, Lihua Xia
The effect of MOOCs learning is closely related to the learning ability of learners. In order to study the change of learners' learning ability, this paper uses hidden Markov model to analyse the continuous learning process of MOOCs learners. Based on the data of learning platform of www.shlll.net, the model is established. The empirical results show that the distinction between learners' high and low learning ability is more obvious. Based on the above findings, this paper further analyses the learning behaviour differences of participants in learning activities and continuous learning. The method proposed in this paper provides a new way for the study of MOOCs learning, which is helpful for the development of MOOCs learning.
{"title":"A hidden Markov model to characterise motivation level in MOOCs learning","authors":"Yuan Chen, Dongmei Han, Lihua Xia","doi":"10.1504/IJCSE.2020.110189","DOIUrl":"https://doi.org/10.1504/IJCSE.2020.110189","url":null,"abstract":"The effect of MOOCs learning is closely related to the learning ability of learners. In order to study the change of learners' learning ability, this paper uses hidden Markov model to analyse the continuous learning process of MOOCs learners. Based on the data of learning platform of www.shlll.net, the model is established. The empirical results show that the distinction between learners' high and low learning ability is more obvious. Based on the above findings, this paper further analyses the learning behaviour differences of participants in learning activities and continuous learning. The method proposed in this paper provides a new way for the study of MOOCs learning, which is helpful for the development of MOOCs learning.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115761512","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031597
Jiayin Zhao, Yong Lu, Hao Ban, Ying Chen
The rapid development of e-commerce has led to the increasing role of satisfaction in more fields. Therefore, the customers' opinion has become a necessary role for the success of related companies. E-commerce satisfaction, as the key factor affecting the performance of e-commerce enterprises, has become a research hotspot in academia. This paper proposes a synthetic evaluation model of satisfaction and logistics performance based on fuzzy synthetic model and dynamic weighted synthetic model respectively. A modified ASCI analysis method based on structured equation model is also proposed to compare with the synthetic method. Beyond this we have also evaluated consumer satisfaction based review data. And corresponding suggestions are given to the operation of e-commerce enterprises.
{"title":"E-commerce satisfaction based on synthetic evaluation theory and neural networks","authors":"Jiayin Zhao, Yong Lu, Hao Ban, Ying Chen","doi":"10.1504/ijcse.2020.10031597","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031597","url":null,"abstract":"The rapid development of e-commerce has led to the increasing role of satisfaction in more fields. Therefore, the customers' opinion has become a necessary role for the success of related companies. E-commerce satisfaction, as the key factor affecting the performance of e-commerce enterprises, has become a research hotspot in academia. This paper proposes a synthetic evaluation model of satisfaction and logistics performance based on fuzzy synthetic model and dynamic weighted synthetic model respectively. A modified ASCI analysis method based on structured equation model is also proposed to compare with the synthetic method. Beyond this we have also evaluated consumer satisfaction based review data. And corresponding suggestions are given to the operation of e-commerce enterprises.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126881805","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031600
Sheng-sheng Wang, Chunshang Xing, Dong Liu
Deep models are structurally tremendous and complex, thus making it hard to deploy on the embedded hardware with restricted memory and computing power. Although, the existing compression methods have pruned the deep models effectively, some issues exist in those methods, such as multiple iterations needed in fine-tuning phase, difficulty in pruning granularity control and numerous hyperparameters needed to set. In this paper, we propose an active stepwise pruning method of a logarithmic function which only needs to set three hyperparameters and a few epochs. We also propose a recovery strategy to repair the incorrect pruning thus ensuring the prediction accuracy of model. Pruning and repairing alternately constitute cyclic process along with updating the weights in layers. Our method can prune the parameters of MobileNet, AlexNet, VGG-16 and ZFNet by a factor of 5.6×, 11.7×, 16.6× and 15× respectively without any accuracy loss, which precedes the existing methods.
{"title":"Efficient deep convolutional model compression with an active stepwise pruning approach","authors":"Sheng-sheng Wang, Chunshang Xing, Dong Liu","doi":"10.1504/ijcse.2020.10031600","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031600","url":null,"abstract":"Deep models are structurally tremendous and complex, thus making it hard to deploy on the embedded hardware with restricted memory and computing power. Although, the existing compression methods have pruned the deep models effectively, some issues exist in those methods, such as multiple iterations needed in fine-tuning phase, difficulty in pruning granularity control and numerous hyperparameters needed to set. In this paper, we propose an active stepwise pruning method of a logarithmic function which only needs to set three hyperparameters and a few epochs. We also propose a recovery strategy to repair the incorrect pruning thus ensuring the prediction accuracy of model. Pruning and repairing alternately constitute cyclic process along with updating the weights in layers. Our method can prune the parameters of MobileNet, AlexNet, VGG-16 and ZFNet by a factor of 5.6×, 11.7×, 16.6× and 15× respectively without any accuracy loss, which precedes the existing methods.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129632091","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031596
C. Guyeux, Jean-Claude Charr, J. B. Abdo, J. Demerjian
Self-avoiding walks (SAWs) have been studied for a long time due to their intrinsic importance and the many application fields in which they operate. A new subset of SAWs, called foldable SAWs, has recently been discovered when investigating two different SAW manipulations embedded within existing protein structure prediction (PSP) software. Since then, several attempts have been made to find out more about these walks, including counting them. However, calculating the number of foldable SAWs appeared as a tough work, and current supercomputers fail to count foldable SAWs of length exceeding ≈ 30 steps. In this article, we present new progress in this enumeration, both theoretical (mathematics) and practical (computer science). A lower bound for the number of foldable SAWs is firstly proposed, by studying a special subset called prudent SAWs that is better known. The triangular and hexagonal lattices are then investigated for the first time, leading to new results about the enumeration of foldable SAWs on such lattices. Finally, a parallel genetic algorithm has been designed to discover new non-foldable SAWs of lengths ≈ 100 steps, and the results obtained with this algorithm are promising.
{"title":"Advances in the enumeration of foldable self-avoiding walks","authors":"C. Guyeux, Jean-Claude Charr, J. B. Abdo, J. Demerjian","doi":"10.1504/ijcse.2020.10031596","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031596","url":null,"abstract":"Self-avoiding walks (SAWs) have been studied for a long time due to their intrinsic importance and the many application fields in which they operate. A new subset of SAWs, called foldable SAWs, has recently been discovered when investigating two different SAW manipulations embedded within existing protein structure prediction (PSP) software. Since then, several attempts have been made to find out more about these walks, including counting them. However, calculating the number of foldable SAWs appeared as a tough work, and current supercomputers fail to count foldable SAWs of length exceeding ≈ 30 steps. In this article, we present new progress in this enumeration, both theoretical (mathematics) and practical (computer science). A lower bound for the number of foldable SAWs is firstly proposed, by studying a special subset called prudent SAWs that is better known. The triangular and hexagonal lattices are then investigated for the first time, leading to new results about the enumeration of foldable SAWs on such lattices. Finally, a parallel genetic algorithm has been designed to discover new non-foldable SAWs of lengths ≈ 100 steps, and the results obtained with this algorithm are promising.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122531307","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031601
Maojun Zhang, Hao Li
In this paper we focus on predicting the yield that is the centrepiece of bond markets. The dynamic Nelson-Siegel model is used to predict the yield of the Chinese corporate bonds with a class of AA, AA+ and AAA ratings. Our empirical results show that this model not only provides good in-sample fit, but also indicates the long-term, medium-term and short-term dynamic features of the yield curve of the corporate bonds with different credit ratings. Finally, we employ AR(1) model to forecast the three factors of the yield curve. Overall, the outcomes are very encouraging for the development of better forecasting systems for fixed income markets.
{"title":"Forecasting the yield of Chinese corporate bonds","authors":"Maojun Zhang, Hao Li","doi":"10.1504/ijcse.2020.10031601","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031601","url":null,"abstract":"In this paper we focus on predicting the yield that is the centrepiece of bond markets. The dynamic Nelson-Siegel model is used to predict the yield of the Chinese corporate bonds with a class of AA, AA+ and AAA ratings. Our empirical results show that this model not only provides good in-sample fit, but also indicates the long-term, medium-term and short-term dynamic features of the yield curve of the corporate bonds with different credit ratings. Finally, we employ AR(1) model to forecast the three factors of the yield curve. Overall, the outcomes are very encouraging for the development of better forecasting systems for fixed income markets.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121951461","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031618
Yanli Wang, Yanyan Feng
Energy balancing and energy efficiency are very important in prolong network life. In wireless sensor networks, cooperative MIMO technology has become a research hotspot in recent years. The appropriate cooperative nodes can transmit data efficiently. Meanwhile, energy harvesting pays attention to the transmission process of network also. This paper presents the selection of cooperative nodes and cluster nodes, which offers energy balance. The node is not only the transmitter of information, but also the transmitter of energy. In addition, the paper also focuses on how to obtain the optimal energy efficiency with proposed resource allocation algorithm. Simulation results show that when cluster nodes and the cooperative nodes are more balanced, the selection algorithm realises the energy balance. The energy efficiency increases rapidly with the amount of transmitted power, and tends to be stable when it reaches 3 dBm. The cooperative MIMO technology is adopted to obtain higher network utility.
{"title":"A new transmission strategy to achieve energy balance and efficiency in wireless sensor networks","authors":"Yanli Wang, Yanyan Feng","doi":"10.1504/ijcse.2020.10031618","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031618","url":null,"abstract":"Energy balancing and energy efficiency are very important in prolong network life. In wireless sensor networks, cooperative MIMO technology has become a research hotspot in recent years. The appropriate cooperative nodes can transmit data efficiently. Meanwhile, energy harvesting pays attention to the transmission process of network also. This paper presents the selection of cooperative nodes and cluster nodes, which offers energy balance. The node is not only the transmitter of information, but also the transmitter of energy. In addition, the paper also focuses on how to obtain the optimal energy efficiency with proposed resource allocation algorithm. Simulation results show that when cluster nodes and the cooperative nodes are more balanced, the selection algorithm realises the energy balance. The energy efficiency increases rapidly with the amount of transmitted power, and tends to be stable when it reaches 3 dBm. The cooperative MIMO technology is adopted to obtain higher network utility.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121900460","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031598
Wangdong Jiang, Yushan Luo, Ying Cao, Guang Sun, C. Gong
In view of the customer churn problem faced by banks, this paper will use the Python language to clean and select the original dataset based on real bank customer data, and gradually condense the 626 customer features in the original dataset to 77 customer features. Then, based on the pre-processed bank data, this paper uses logistic regression, decision tree and neural network to establish three bank customer churn warning models and compares them. The results show that the accuracy of the three models in predicting bank loss customers is above 92%. Finally, based on the logistic regression model with better evaluation results, this paper analyses the characteristics of the lost customers for the bank, and gives the bank management suggestions for the lost customers.
{"title":"On the build and application of bank customer churn warning model","authors":"Wangdong Jiang, Yushan Luo, Ying Cao, Guang Sun, C. Gong","doi":"10.1504/ijcse.2020.10031598","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031598","url":null,"abstract":"In view of the customer churn problem faced by banks, this paper will use the Python language to clean and select the original dataset based on real bank customer data, and gradually condense the 626 customer features in the original dataset to 77 customer features. Then, based on the pre-processed bank data, this paper uses logistic regression, decision tree and neural network to establish three bank customer churn warning models and compares them. The results show that the accuracy of the three models in predicting bank loss customers is above 92%. Finally, based on the logistic regression model with better evaluation results, this paper analyses the characteristics of the lost customers for the bank, and gives the bank management suggestions for the lost customers.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"494 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127579628","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 : 2020-08-26DOI: 10.1504/ijcse.2020.10031602
Wei Chen, Kun Zhou, Weidong Fang, Ke Wang, Fangming Bi, Biruk Assefa
Blockchain is a widely used decentralised infrastructure. Blockchain technology has the decentration of network, the unforgeability of block data, etc. Therefore, blockchain technology has developed rapidly in recent years, and many organisations are involved. Applications are generally optimistic. This paper systematically introduces the background development status of blockchain, and analyses the operation mechanism, characteristics and possible application scenarios of blockchain technology from a technical perspective. Finally, the blockchain technology is applied to the intellectual property protection method as an example to study domestic and foreign examples and analyse existing problems. The review article aims to provide assistance for the application of blockchain technology.
{"title":"Review on blockchain technology and its application to the simple analysis of intellectual property protection","authors":"Wei Chen, Kun Zhou, Weidong Fang, Ke Wang, Fangming Bi, Biruk Assefa","doi":"10.1504/ijcse.2020.10031602","DOIUrl":"https://doi.org/10.1504/ijcse.2020.10031602","url":null,"abstract":"Blockchain is a widely used decentralised infrastructure. Blockchain technology has the decentration of network, the unforgeability of block data, etc. Therefore, blockchain technology has developed rapidly in recent years, and many organisations are involved. Applications are generally optimistic. This paper systematically introduces the background development status of blockchain, and analyses the operation mechanism, characteristics and possible application scenarios of blockchain technology from a technical perspective. Finally, the blockchain technology is applied to the intellectual property protection method as an example to study domestic and foreign examples and analyse existing problems. The review article aims to provide assistance for the application of blockchain technology.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131351606","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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