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2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)最新文献

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Protocol Programming: A Layered Programming Paradigm 协议编程:分层编程范式
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00058
Yanping Chen, Zehua Ding, Q. Zheng, Bin Liu, N. Shah
{"title":"Protocol Programming: A Layered Programming Paradigm","authors":"Yanping Chen, Zehua Ding, Q. Zheng, Bin Liu, N. Shah","doi":"10.1109/ICEBE.2018.00058","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00058","url":null,"abstract":"Modularized programming has many advantages. However, the current encapsulation makes a hard partition between modules. It is weak in communication. In this paper, a layered programming paradigm is presented, where \"layer\" is an abstract interface to support functional partitioning. Under this paradigm, all instantiated modules are automatically connected to a thread network, which provide a platform for communication. Protocols are defined to coordinate the behaviours between them and control mechanisms, such as concurrency, parallelism, distribution and pipeline, etc. An implementation is presented to show the effectiveness of protocol programming.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130003886","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
Meta-Feature Based Data Mining Service Selection and Recommendation Using Machine Learning Models 基于元特征的数据挖掘服务选择与推荐
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00014
Bayan I. Alghofaily, Chen Ding
{"title":"Meta-Feature Based Data Mining Service Selection and Recommendation Using Machine Learning Models","authors":"Bayan I. Alghofaily, Chen Ding","doi":"10.1109/ICEBE.2018.00014","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00014","url":null,"abstract":"Abstract-Quality of Service (QoS) based web service selection has been studied in the service computing community for some time. However, characteristics of the input dataset are not usually considered in the selection process, even though they might have an impact on the QoS values of the service. To address this issue, we propose a QoS-based service selection process that considers the impact of dataset features and we focus on data mining services because their QoS values could be highly dependent on dataset features. We have used a meta-learning algorithm to incorporate dataset features in the selection process and studied the use of different machine learning algorithms (both classification models and regression models) as meta-learners in recommending data mining services for the given dataset. We have also investigated the impact of the number of dataset features on the performance of the meta-learners. Out of the five classification models examined here, Support Vector Machine (SVM) showed the best results in predicting the recommended service for the given dataset with an accuracy of 78%. When it comes to regression models, Multilayer Perceptron (MLP) was the best regressor. We recommend considering only simple meta-features that can be collected for most datasets, as those proved to be sufficient to achieve good prediction accuracy.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129785955","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
Intelligent Risk Management Framework for BYOD 智能BYOD风险管理框架
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00055
Khoula Al Harthy, N. Shah, Arun Shankarappa
{"title":"Intelligent Risk Management Framework for BYOD","authors":"Khoula Al Harthy, N. Shah, Arun Shankarappa","doi":"10.1109/ICEBE.2018.00055","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00055","url":null,"abstract":"The current information security risk management systems mainly focus on networking related risks that apply to network devices and users. However, risk management landscape has changed in recent years as new smart, mobile devices have been incorporated into the business networks to enhance productivity. This new phenomenon is called Bring Your Own Devices (BYOD) environment. The traditional risk management plans suffer from emerging threats that exist in BOYD environment. It is imperative to have an effective risk management system for the BOYD environment to efficiently deal with privacy breaches loss of business data and data leakage. Therefore, this paper proposes a novel approach which utilizes MDM log file to proactively detect potential threats in BYOD environment and take preventive and mitigative measures in real time.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116433020","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: 7
Yet Another Blockchain Use Case – The Label Chain 另一个区块链用例——标签链
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00037
Thomas Keller, Nik Kessler
{"title":"Yet Another Blockchain Use Case – The Label Chain","authors":"Thomas Keller, Nik Kessler","doi":"10.1109/ICEBE.2018.00037","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00037","url":null,"abstract":"Based on a data provenance use case, the use of a blockchain is derived and critically evaluated. All core functions of the concept have been successfully implemented in the technical implementation of the prototype. However, the question arose as to how far the technologies are ready for productive use.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122121266","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
Toward a Self-Learned Smart Contracts 走向自我学习的智能合约
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00051
Ahmed S. Almasoud, Maged M. Eljazzar, F. Hussain
{"title":"Toward a Self-Learned Smart Contracts","authors":"Ahmed S. Almasoud, Maged M. Eljazzar, F. Hussain","doi":"10.1109/ICEBE.2018.00051","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00051","url":null,"abstract":"In recent years, Blockchain technology has been highly valued and disruptive. Several researches have presented a merge between blockchain and current application i.e. medical, supply chain, and e-commerce. Although Blockchain architecture does not have a standard yet, IBM, MS, AWS offer BaaS (Blockchain as a Service). In addition to the current public chains i.e. Ethereum, NEO, and Cardeno; there are some differences between several public ledgers in terms of development and architecture. This paper introduces the main factors that affect integration of Artificial Intelligence with Blockchain. As well as, how it could be integrated for forecasting and automating; building self-regulated chain.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125449776","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: 8
Cloud Service Composition with Multiple QoS Constraints for Manufacturing Resource 制造资源多QoS约束的云服务组合
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00033
Guo-dong Yi, Hangjian Hu, Shuyou Zhang, Long Sun
{"title":"Cloud Service Composition with Multiple QoS Constraints for Manufacturing Resource","authors":"Guo-dong Yi, Hangjian Hu, Shuyou Zhang, Long Sun","doi":"10.1109/ICEBE.2018.00033","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00033","url":null,"abstract":"Quality of Service (QoS) plays an important role in cloud services, and a service composition method with multiple QoS constraints for manufacturing resource is presented. Based on the description of the QoS of cloud service, a decomposition method based on Hierarchical Task Network (HTN) planning is proposed to decompose manufacturing tasks into atomic tasks, which are used as user requests to match cloud services in the cloud service pool through interface semantics. A combination process of cloud service is established, which treats the service corresponding to each atomic task as an independent component service, and completes the manufacturing task by forming a more powerful and complete combined cloud service through interface semantic matching. The method proposed in this paper helps to solve the problem of low quality and slow speed of matching in the process of manufacturing resource cloud service.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130242712","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
Artificial Intelligence and Mobile Phone Sensing Based User Activity Recognition 基于人工智能和手机感知的用户活动识别
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00034
Chia-Liang Chen, F. Huang, Yu-Hsin Liu, Dai-En Wu
{"title":"Artificial Intelligence and Mobile Phone Sensing Based User Activity Recognition","authors":"Chia-Liang Chen, F. Huang, Yu-Hsin Liu, Dai-En Wu","doi":"10.1109/ICEBE.2018.00034","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00034","url":null,"abstract":"With the development of Micro Electro Mechanical Systems, a growing number of portable devices and wearable devices equipped with built-in sensors, which can detect the physical movements, such as identifying the action type and record the duration of exercise. Since the amount of data collected from sensors grows, automatic activity recognition becomes an important issue to living in a smart life. Therefore, this paper aims to use various kinds of machine learning techniques to build the automatic activity classification model, including Logistic regression, Decision tree, Random forest and Support vector machine algorism. Furthermore, we evaluated the prediction performance of four supervised machine learning classification models. Results of the experiments show that under specific acceptance of accuracy and minimum model training time, the decision tree algorithm creates the best model. However, if consider the accuracy as the only pursue, adopting the support vector machine algorithm will get the better model.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117075399","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
Prediction of Crowdfunding Project Success with Deep Learning 用深度学习预测众筹项目的成功
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00012
Pi-Fen Yu, F. Huang, Chuan Yang, Yu-Hsin Liu, Zi-Yi Li, Cheng-Rung Tsai
{"title":"Prediction of Crowdfunding Project Success with Deep Learning","authors":"Pi-Fen Yu, F. Huang, Chuan Yang, Yu-Hsin Liu, Zi-Yi Li, Cheng-Rung Tsai","doi":"10.1109/ICEBE.2018.00012","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00012","url":null,"abstract":"Over the past century there has been a dramatic increase in crowdfunding activity, which offers an alternative for both creators and backers to sell products and invest in creative businesses respectively. However, empirical analysis shows that only one-third of crowdfunding campaigns could meet their fundraising goal. The aim of this paper is to develop a model that predicts the success of crowdfunding project with deep learning. The datasets are retrospectively collected from Kaggle and contain historical records of Kickstarter campaigns. The model could provide insights in pre-lunching stage and in early stage of fundraising. The proposed MLP model can provide accountable results when applied to different crowdfunding platforms that have not been addressed before. Comprehensive experiments are conducted and a variety of classification algorithms have been tested to support this prediction engine and they concluded that the MLP model has the best outcome with the highest degree of confidence.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130706429","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: 19
Customised Data Dashboard for Contact Centres by Focussing on Customer Identification 通过关注客户识别，为联络中心定制数据仪表板
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00032
Morteza Saberi, Elizabeth Chang, M. Saffari, O. Hussain
{"title":"Customised Data Dashboard for Contact Centres by Focussing on Customer Identification","authors":"Morteza Saberi, Elizabeth Chang, M. Saffari, O. Hussain","doi":"10.1109/ICEBE.2018.00032","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00032","url":null,"abstract":"The main touch point of any organisation is its Contact Centre (CC) where about seventy percent of all customer interactions are handled. The first task of these centres is customer recognition. Wrong identification leads to customer dissatisfaction, which consequently affects Customer Service Representatives' (CSRs) emotions. CSR fatigue is a known problem in CCs and one of their main issues is the high rate of CSR attrition. Therefore, CSRs need good support such as having the required valuable information within CCs along with advanced data analytic tools and techniques that make their job of customer identification more efficient. In this paper, we propose a customised Customer Identification (ID) dashboard that provides a summary of customers' profiles to the CSRs. We propose a heuristic algorithm which measures the difficulty of customer identification based on his/her name. This information allows the CSR to know beforehand how much effort is required to ensure that the customer is identified as quickly as possible.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121929094","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
A Hybrid Decision Model for Heterogeneous Schemes in "Internet Plus" Hackerspace Product Development “互联网+”创客空间产品开发中异构方案的混合决策模型
2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00020
Ye Gu, Shuyou Zhang
{"title":"A Hybrid Decision Model for Heterogeneous Schemes in \"Internet Plus\" Hackerspace Product Development","authors":"Ye Gu, Shuyou Zhang","doi":"10.1109/ICEBE.2018.00020","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00020","url":null,"abstract":"Hackerspace product development helps use the collective intelligence for new product development under the \"Internet plus\" environment. However, the schemes from the designer collective are numerous, diverse and heterogeneous, how to select the valuable schemes rapidly and intelligently is an inevitable challenge. This paper attempts to propose a hybrid decision model for heterogeneous schemes. Firstly, a hackerspace product development framework is given out based on the \"Internet plus\" environment, and the schemes decision model is one of the most important components. Secondly, by analyzing the heterogeneous schemes including textual descriptions, sketches and CAD models, three different feature vectors are introduced and combined as a joint computer-aided decision model. Then, a group decision-making model in voting-based method is added for the hybrid model. Finally, an illustrative example is studied to confirm the feasibility of the proposed model in engineering applications.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125092592","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
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