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2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)最新文献

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A Case Study of Predicting Banking Customers Behaviour by Using Data Mining 基于数据挖掘的银行客户行为预测案例研究
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963436
Xujuan Zhou, Ghazal Bargshady, Moloud Abdar, Xiaohui Tao, R. Gururajan, K. C. Chan
{"title":"A Case Study of Predicting Banking Customers Behaviour by Using Data Mining","authors":"Xujuan Zhou, Ghazal Bargshady, Moloud Abdar, Xiaohui Tao, R. Gururajan, K. C. Chan","doi":"10.1109/BESC48373.2019.8963436","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963436","url":null,"abstract":"Data Mining (DM) is a technique that examines information stored in large database or data warehouse and find the patterns or trends in the data that are not yet known or suspected. DM techniques have been applied to a variety of different domains including Customer Relationship Management CRM). In this research, a new Customer Knowledge Management (CKM) framework based on data mining is proposed. The proposed data mining framework in this study manages relationships between banking organizations and their customers. Two typical data mining techniques - Neural Network and Association Rules - are applied to predict the behavior of customers and to increase the decision-making processes for recalling valued customers in banking industries. The experiments on the real world dataset are conducted and the different metrics are used to evaluate the performances of the two data mining models. The results indicate that the Neural Network model achieves better accuracy but takes longer time to train the model.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125087577","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}
引用次数: 3
Object-based Image Discrimination Relationship Recognition 基于目标的图像判别关系识别
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963477
Yan Li, Baopeng Zhang, Jiajie Tian, Rui Li, Sibo Wang, Jianping Fan
{"title":"Object-based Image Discrimination Relationship Recognition","authors":"Yan Li, Baopeng Zhang, Jiajie Tian, Rui Li, Sibo Wang, Jianping Fan","doi":"10.1109/BESC48373.2019.8963477","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963477","url":null,"abstract":"With the development of self-media, we can publish images freely on the Internet, and there will be some discriminatory images more or less. Discrimination is an emotional relationship. However, there is no open data set to help us complete the task of discriminatory image detection. In this article, we created a simple data set that can be used to detect discriminatory relationships. Then, on this data set, we propose a baseline for discriminatory relationship detection. This baseline is a multi-task network based on translation embedding model, which can output both the action categories of objects in the graph and the relationship categories between the two. Experiments show that our multi-task network can effectively detect relationships, and it is better than the simple translation embedding model.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123080303","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}
引用次数: 0
Actively Semi-Supervised Collaborative Filtering 主动半监督协同过滤
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963018
Wei Cui, Jun Wu
{"title":"Actively Semi-Supervised Collaborative Filtering","authors":"Wei Cui, Jun Wu","doi":"10.1109/BESC48373.2019.8963018","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963018","url":null,"abstract":"Collaborative filtering (CF) has been widely used in various recommender systems, but often suffers from the problem of data sparsity which dramatically degrades the recommendation performance. In this paper, we propose a co-training style semi-supervised CF approach towards the task of rating prediction, which exploits a few observed ratings in conjunction with copious unobserved ones to reduce sparsity. In each round of co-training iterations, our approach utilizes two different neighborhood-based recommenders, each of which labels the unobserved data for the other recommender; in particular, the most informative unobserved examples are actively selected for labeling, and then the labeling confidence is estimated through validating the influence of the labeling of unobserved examples on the observed ones. Experiments results on the three datasets demonstrate that our approach can effectively exploit unobserved data to improve CF predictions, and achieves better performance than other counterparts.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130721092","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}
引用次数: 1
Improved Biclustering Algorithm Based on Weighted Mean Square Residual 基于加权均方残差的改进双聚类算法
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963098
Wenhua Liu, Yaxin Hou, Yidong Li, Hongwei Zhao
{"title":"Improved Biclustering Algorithm Based on Weighted Mean Square Residual","authors":"Wenhua Liu, Yaxin Hou, Yidong Li, Hongwei Zhao","doi":"10.1109/BESC48373.2019.8963098","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963098","url":null,"abstract":"Microarrays are one of the latest breakthroughs in experimental molecular biology, which have already provided huge amount of high dimensional genetic data. Existing biclustering algorithms can hardly discover biclusters with overlapping structures. Consequently, the correct bicluster structures hidden in gene expression data cannot be effectively found. Moreover, the influence of the importance of the different conditions on the bicustering result is not taken into account in the process of adding and deleting conditions. An improved biclustering algorithm based on weighted mean square residual (IBWMSR) is proposed to overcome the above defects. Our algorithm also proposes a new objective function to update weights of each bicluster, which can simultaneously select the conditions set of each bicluster using some rules. The gene sets are firstly partitioned into initial biclusters by using fuzzy partition and the fuzzy partition is controlled by overlapping ratio and the membership of the genes. Then, the weights of the conditions in each bicluster are iteratively updated in the process of minimizing the objective function. Finally, the bicluster set is obtained after adding the genes satisfying the constraints and removing the genes producing inconsistency fluctuation. The experiment shows that the proposed algorithm generates the biclusters with similar expression level of different sizes and restricts the overlapping ratio to a reasonable range and generate larger biclusters with lower mean square residues.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128437481","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}
引用次数: 0
Vehicle Detection in Distorted Driving Video Based on Metric Learning and Single Shot MultiBox Detector 基于度量学习和单镜头多盒检测器的失真驾驶视频车辆检测
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963547
Fanghui Zhang, Yi Jin, Shichao Kan, Linna Zhang, Y. Cen, Jin Wen
{"title":"Vehicle Detection in Distorted Driving Video Based on Metric Learning and Single Shot MultiBox Detector","authors":"Fanghui Zhang, Yi Jin, Shichao Kan, Linna Zhang, Y. Cen, Jin Wen","doi":"10.1109/BESC48373.2019.8963547","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963547","url":null,"abstract":"With the gradually development of deep learning, the object detection algorithm has achieved remarkable applications, especially in the aspect of the automatic driving. Most of the object detection algorithms are used for pictures or videos obtained by a general camera. In practice, fisheye cameras are widely used, which will produce distorted image frames. The research of vehicle detection based on fisheye camera is relatively rare until now. If one network is trained on the existed public dataset, and tested on the distorted images or videos, the accuracy will decrease a lot. Thus, a distorted vehicle dataset needs to be manually labeled in the first. However, if we only use the distorted vehicle dataset to train the model, the mount of the distorted vehicle dataset is small, meanwhile the public datasets will not be fully used. On the other hand, the missing detection and false detection for the distorted images by using SSD algorithm is a considerable problem. Based on those considerations, firstly, transfer learning is adopted to transfer the parameters learned from the public vehicle dataset to the distorted vehicle dataset in this paper. Secondly, an algorithm named MLSSD for the distorted vehicle detection based on the labeled dataset is proposed to achieve a better performance for the vehicle detection, which mainly combines metric learning and SSD algorithm to enormously alleviate the missing detection and false detection. In addition, the scalable overlapping partition pooling (SOPP) method is proposed instead of the spatial pyramid pooling to achieve more robust feature map pooling. Experimental results show that the proposed MLSSD algorithm significantly outperforms other algorithms and achieves 88.3 % mAP on the distorted vehicle dataset, 3.1% more than the result obtained by the SSD network.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128110641","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}
引用次数: 1
GA for QoS Satisfaction Degree Optimal Web Service Composition Selection Model 基于遗传算法的QoS满意度最优Web服务组合选择模型
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8962994
Minghua Chen, Qingjun Wang, Wei Sun, Xiaoying Song, Na Chu
{"title":"GA for QoS Satisfaction Degree Optimal Web Service Composition Selection Model","authors":"Minghua Chen, Qingjun Wang, Wei Sun, Xiaoying Song, Na Chu","doi":"10.1109/BESC48373.2019.8962994","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8962994","url":null,"abstract":"As the Web service technology is using more widely in cloud computing, the Web service composition selection has also become one of the most popular research fields. The service composition selection problem is described as an multi-objective optimization problem considering multi QoS parameters and solved by an intelligent optimization algorithm in most of the existing literatures. Feelings of the users are usually ignored. In this paper, the concept of QoS satisfaction degree is introduced and adopted as the optimal objective of the Web service composition selection model. Genetic algorithm (GA) is applied to solve the problem and test result show that the solution prompted in this paper is feasible and effective.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115934952","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}
引用次数: 4
The Effect of Urbanization Quality on Resident Consumption in China 中国城市化质量对居民消费的影响
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8962980
M. Wei, Xiqin Hu, Wenwen Qin, Kai Xu
{"title":"The Effect of Urbanization Quality on Resident Consumption in China","authors":"M. Wei, Xiqin Hu, Wenwen Qin, Kai Xu","doi":"10.1109/BESC48373.2019.8962980","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8962980","url":null,"abstract":"Urbanization is an effective way to promote resident consumption. Based on the evaluation of urbanization quality in China, this paper empirically analyzes the impact of urbanization quality on resident consumption by using panel data of 30 provinces (regions) from 2005 to 2017. The results show that the improvement of urbanization quality can enhance residents' income level, change their consumption concept and improve the consumption environment, and then promote resident consumption. From sub-regional view, urbanization quality has a positive impact on resident consumption in the eastern, central and western regions, nevertheless the impact in the eastern region is most significant.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"291 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122712391","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}
引用次数: 0
Entropy-Based Model Selection Using Monte Carlo Method 基于熵的蒙特卡罗方法模型选择
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963133
Masaki Satoh, T. Miura
{"title":"Entropy-Based Model Selection Using Monte Carlo Method","authors":"Masaki Satoh, T. Miura","doi":"10.1109/BESC48373.2019.8963133","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963133","url":null,"abstract":"In this investigation, we propose a new kind of simplification specialized for Multiple Regression Analysis (MRA) using Random sampling. We propose a novel approach to simplify MRA models for dimension reduction while preserving amount of information. After applying Principle Component Analysis (PCA) to explanatory variables of interests to simplify relationship among them, we reduce the variables (dimensions) quickly to avoid loss of entropy in an efficient manner. We show an experimental results to see the effectiveness of this approach. Our main idea comes from random sampling with the tight relationship between entropy and multiple correlation coefficients (MCC).","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129103796","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}
引用次数: 0
User Behavior Redibility Evaluation Model Based on AHP and Rough Set and Game Theory 基于层次分析法、粗糙集和博弈论的用户行为可信度评估模型
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963258
Haidong Cui, Z. Feng, Dongfang Ma
{"title":"User Behavior Redibility Evaluation Model Based on AHP and Rough Set and Game Theory","authors":"Haidong Cui, Z. Feng, Dongfang Ma","doi":"10.1109/BESC48373.2019.8963258","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963258","url":null,"abstract":"In order to solve the problem that traditional user behavior trustworthiness assessment methods are too subjective and have poor dynamic adaptability when setting classification weight, in this paper, the traditional Analytic Hierarchy Process has been optimized and improved, a new trustworthiness evaluation model of user behavior based on improved AHP, rough set and game theory is proposed. This method combines user activity, reward and punishment factors to evaluate user behavior comprehensively, so that the evaluation results are more scientific and accurate. and demonstrates the feasibility of the method by an example. The results show that the evaluation model can adapt to the dynamic changes in user behavior trust, objectively determine the weight of each decision attribute, and can accurately and effectively assess the credibility of user behavior.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128584028","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}
引用次数: 1
Corruption and enterprise innovation under the background of transition in China 中国转型背景下的腐败与企业创新
2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963024
Q. Jiang, Oinamei Tan
{"title":"Corruption and enterprise innovation under the background of transition in China","authors":"Q. Jiang, Oinamei Tan","doi":"10.1109/BESC48373.2019.8963024","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963024","url":null,"abstract":"In recent years, both corruption and economic growth have earned substantial attention from scholars, but the relationship between corruption and enterprise innovation has not received sufficient attention in the current literature. Using the World Bank's (WB) survey data on the environmental quality of Chinese enterprises' operating systems, this paper empirically studied the relationship between corruption and enterprise innovation. The results show that corruption promotes enterprise innovation, and corruption has significant different impacts on the innovation of enterprises with different sizes. The results indicate a robust relationship between corruption and enterprise innovation.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116387191","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}
引用次数: 3
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