2015 IEEE 12th International Conference on e-Business Engineering最新文献_第2页

A Queuing-Network-Based Approach to Performance Evaluation of Service Compositions 基于排队网络的服务组合性能评价方法

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.31

Gang Zhou, Yunni Xia, K. Yu, Qiang Chen, Ping Gu

引用次数: 0

A Framework for Workload-Aware Views Materialisation of Semantic Databases 语义数据库工作负载感知视图实体化框架

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.13

Tomasz Zlamaniec, K. Chao, Nick Godwin, N. Shah, Raymond Farmer

{"title":"A Framework for Workload-Aware Views Materialisation of Semantic Databases","authors":"Tomasz Zlamaniec, K. Chao, Nick Godwin, N. Shah, Raymond Farmer","doi":"10.1109/ICEBE.2015.13","DOIUrl":"https://doi.org/10.1109/ICEBE.2015.13","url":null,"abstract":"Views materialisation is well known in the context of relational databases. However, unlike relational databases, the semantic graph model lacks restrictive structure. Instead, the semantic data rely on an evolving schema. This resulted in a challenge for views materialisation while allowing for open repositories of data to emerge. Open repositories combine knowledge from many different areas. Therefore, it can be assumed that various data structures within a repository may exhibit different daily access patterns, i.e. That the user interests change during the day. This research verifies this assumption and proposes a new views selection model. By analysing how access patterns of individual views contribute to the overall system workload, the proposed model aims at selection of candidates offering the highest reduction of the peak workload. The proposed selection method has been integrated as a part of a new optimisation framework, which operates as a proxy for a SPARQL-enabled database. The approach has a potential to accelerate the adaptation of views materialisation for SPARQL. The proposed approach is evaluated both experimentally and using qualitative analysis.","PeriodicalId":153535,"journal":{"name":"2015 IEEE 12th International Conference on e-Business Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121355385","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

Attribute-Based Encryption Goes X.509 基于属性的加密采用X.509

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.73

Florian Reimair, Johannes Feichtner, Peter Teufl

引用次数: 7

A Recommendation System for Travel Services Based on Cyber-Anima 基于网络动物的旅游服务推荐系统

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.28

Mi Zhang, Yinsheng Li, Aiqin Zhou, Zhou Fang

引用次数: 2

Common Features Based Volunteer and Voluntary Activity Recommendation Algorithm 基于共性特征的志愿者及志愿者活动推荐算法

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.17

Feng Tian, Yan Chen, Xiaoqian Wang, Tian Lan, Q. Zheng, K. Chao

{"title":"Common Features Based Volunteer and Voluntary Activity Recommendation Algorithm","authors":"Feng Tian, Yan Chen, Xiaoqian Wang, Tian Lan, Q. Zheng, K. Chao","doi":"10.1109/ICEBE.2015.17","DOIUrl":"https://doi.org/10.1109/ICEBE.2015.17","url":null,"abstract":"In general, the dataset of volunteer recommendation systems shows the sparsity, while a volunteer recommendation system required performing the function of recommending voluntary activities interesting to a specific volunteer. To our knowledge, there exists no such kind of recommendation systems. To begin with, this paper firstly presents an analysis of a dataset collected from a real volunteering application website and discovered two features: the locations between the volunteers and the voluntary activities are in close proximity, and the resulting graph which describes the participation relationship between volunteers and voluntary activities is a kind of bipartite, showing many small communities inside it. We call the first discovery 'geographically closely participating', and the second discovery 'participating together'. Based on these findings, a rating matrix, featuring a matching method for the recommendation algorithm has been constructed. Secondly, we propose a weighted Personal Rank algorithm to implement the required functions of a volunteer recommendation system by employing the registration information of volunteers and voluntary activities. This includes the volunteers' preferences, activities and location etc. The comparison of proposed method with the rating matrix-based collaborative filter algorithm and the Personal Rank algorithms shows that our proposed method outperforms them.","PeriodicalId":153535,"journal":{"name":"2015 IEEE 12th International Conference on e-Business Engineering","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115223025","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: 5

Relaxation Based SaaS for Repairing Failed Queries over the Cloud Computing 基于松弛的SaaS在云计算上修复失败查询

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.49

Abderrahim Ait Wakrime, S. Benbernou, Saïd Jabbour

引用次数: 9

A Heuristic Resource Scheduling Algorithm of Cloud Computing Based on Polygons Correlation Calculation 基于多边形关联计算的云计算启发式资源调度算法

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.68

Jingnan Tang, Liang Luo, Kai-Ming Wei, Xun Guo, Xiao-yu Ji

{"title":"A Heuristic Resource Scheduling Algorithm of Cloud Computing Based on Polygons Correlation Calculation","authors":"Jingnan Tang, Liang Luo, Kai-Ming Wei, Xun Guo, Xiao-yu Ji","doi":"10.1109/ICEBE.2015.68","DOIUrl":"https://doi.org/10.1109/ICEBE.2015.68","url":null,"abstract":"Cloud computing provides utility-oriented IT services for users worldwide, and it enables offering various kinds of applications to consumer in scientific or business field based on a pay-as-you-go model. Although cloud computing is still in its infancy, the scale of cloud infrastructure is expanding fast, which result in huge energy consumption and operating costs. Due to the complex architecture of cloud infrastructure, it is hard to evaluate and optimize energy consumption of cloud infrastructure in a non-intrusive manner under varying application, user configurations and requirements. In this paper, we present Bin-Balancing Algorithm (BBA), an innovative resource scheduling algorithm for private clouds that integrating the advantages of both bin packing solutions and polygons correlation calculations. BBA is designed to optimize energy consumption, while considering the task deadline, host PE (processing element), memory and bandwidth. Polygons correlation calculation integrated in BBA is used to meet the elastic characteristics of cloud computing services. BBA is validated and well compared with existing resource scheduling algorithms in Cloud Sim toolkit. The results demonstrate that BBA can save energy in cloud infrastructure while balancing the loss of performance and SLA of cloud users.","PeriodicalId":153535,"journal":{"name":"2015 IEEE 12th International Conference on e-Business Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127557459","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

Integration of Sensors to Improve Customer Experience: Implementing Device Integration for the Retail Sector 集成传感器以改善客户体验:实现零售部门的设备集成

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.71

Mark Anderson, Joseph Bolton

{"title":"Integration of Sensors to Improve Customer Experience: Implementing Device Integration for the Retail Sector","authors":"Mark Anderson, Joseph Bolton","doi":"10.1109/ICEBE.2015.71","DOIUrl":"https://doi.org/10.1109/ICEBE.2015.71","url":null,"abstract":"Within the retail sector, a broad range of sensing devices are used to capture data to be interpreted into retail intelligence. The sensors many capture simplified data sets, such as the number of customers who have walked through a doorway or down an aisle, to more complex data, such as demographic or behavioural data. For a retailer this provides an opportunity of analyzing a rich source of information to optimize the customer experience and thereby improve sales. However, the sensors that are deployed are typically manufactured by different vendors, and may be installed over an extended period of time. This leads to difficulties when integrating and triangulating the data in an automated system as each retailer may have a bespoke collection of capture devices. This paper reports upon a project to overcome these challenges through the adoption of approaches taken in Field Device Integration (FDI), commonly used to integrate sensors and actuators in a manufacturing environment. The paper proposes an architectural model based on investigative work, and also discusses a related issue that has arisen in the implementation of the framework, that of multitenancy.","PeriodicalId":153535,"journal":{"name":"2015 IEEE 12th International Conference on e-Business Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129487717","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: 14

Learning Factor Selection for Boosted Matrix Factorisation in Recommender Systems 推荐系统中增强矩阵分解的学习因子选择

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.18

N. Chowdhury, Xiongcai Cai, Cheng Luo

{"title":"Learning Factor Selection for Boosted Matrix Factorisation in Recommender Systems","authors":"N. Chowdhury, Xiongcai Cai, Cheng Luo","doi":"10.1109/ICEBE.2015.18","DOIUrl":"https://doi.org/10.1109/ICEBE.2015.18","url":null,"abstract":"Matrix factorisation (MF), an effective recommendation algorithm, predicts user preferences on items based on the historical preferences of other like-minded users. Classical MF methods do not explicitly distinguish the significances across the underlying factors that determine a users' preference on an item. The identical contribution of latent factors during learning results unnecessary updates on unimportant variables that leads to slower and suboptimal convergence. In this paper, we propose a new matrix factorisation method that not only seeks the intrinsic and outstanding factors that determine the users' preferences but also systematically reinforces the contribution generated by these factors. Based on boosting, a factor selection mechanism is developed to account the variable importance of latent factors to generate an ensemble recommender on the selected subspace of the latent factors by the principle of model uncertainty reduction. The proposed method is evaluated against a variety of the state-of-the-art methods of recommender systems on three publicly available benchmark datasets. The results confirm the effectiveness and efficiency of the proposed method.","PeriodicalId":153535,"journal":{"name":"2015 IEEE 12th International Conference on e-Business Engineering","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134475266","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

Research on mobile readers' continuance intention: A reading type perspective 基于阅读类型视角的移动读者延续意向研究

2015 IEEE 12th International Conference on e-Business Engineering Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.56

Xiao Jiang

引用次数: 1