2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)最新文献_第9页

A neighbor selection method based on network community detection for collaborative filtering 基于网络社区检测的协同过滤邻居选择方法

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-04 DOI: 10.1109/ICIS.2014.6912122

Lin-Rong Guo, Qinke Peng

{"title":"A neighbor selection method based on network community detection for collaborative filtering","authors":"Lin-Rong Guo, Qinke Peng","doi":"10.1109/ICIS.2014.6912122","DOIUrl":"https://doi.org/10.1109/ICIS.2014.6912122","url":null,"abstract":"The neighbor selection that determines which users are exploited to estimate a target user's ratings has an important influence on the accuracy of recommendations of collaborative filtering based recommender system. Two kinds of ways for neighbor selection: KNN and cluster-based, are lack of specificity which refers to selecting different appropriate neighbors for different given target users, and thus limit the accuracy of recommendation. Therefore, in this paper, firstly, we propose a method that employs the evolutionary algorithm to optimize neighbors for all target users. Secondly, overcoming the high time complexity of the first one, we present another approach in which community detection algorithm is utilized as a preprocessing, and then the evolution algorithm is employed to optimize the neighborhood size for every community. We present experiments on a standard benchmark data-set, and the results show that the two methods both realize the specificity in neighbor selection, and accordingly lead to a higher accuracy of recommendations. Besides, the second one makes a good compromise between the specificity and time complexity.","PeriodicalId":237256,"journal":{"name":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123937782","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

Geometry based visualization of hierarchical structures 基于几何的层次结构可视化

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-04 DOI: 10.1109/ICIS.2014.6912178

Pengcheng Wang, Kang Zhang, Xiao-Xu Song, Tianyi Zhou, Dongwei Gong

引用次数: 2

Simulation of a Semantic Web data sharing system based on NS-3 基于NS-3的语义Web数据共享系统仿真

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-04 DOI: 10.1109/ICIS.2014.6912168

Qi Huang, Jing Zhou, Lei Shi, Wei Yan

引用次数: 1

Profit-driven resource scheduling for virtualized cloud systems 虚拟化云系统的利润驱动资源调度

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-04 DOI: 10.1109/ICIS.2014.6912145

Shiyang Ye, Tao Wang, Wen-bo Zhang, Hua Zhong

{"title":"Profit-driven resource scheduling for virtualized cloud systems","authors":"Shiyang Ye, Tao Wang, Wen-bo Zhang, Hua Zhong","doi":"10.1109/ICIS.2014.6912145","DOIUrl":"https://doi.org/10.1109/ICIS.2014.6912145","url":null,"abstract":"Virtualized resource renting is a key issue in IaaS (Infrastructure-as-a-Service) cloud systems. Suitable resource allocation improves resource utilization and increases profit for application providers. The application provider will obtain better revenues according to the Service Level Agreement (SLA), if they rent more virtual resources. However, they will invest much more capital for renting these virtual resources. How many resources a provider rents has become a key thing for cloud applications. This paper addresses the reconciliation objectives by proposing a profit-driven resource scheduling method for virtualized cloud systems. Compared with traditional methods, our method aims at maximizing the revenues by introducing SLA and the cost of renting cloud resource, instead of increasing resource utilization or decreasing early finishing time. We model the performance of applications with queueing theory; calculate the revenues according to the SLA and renting cost; adjust the amount of virtual resources to adapt to dynamic workloads in period. We have implemented a framework for scheduling virtual resources, and applied it in our IaaS cloud platform OnceCloud. The experimental results demonstrate that our method has advantages over existing ones in revenues.","PeriodicalId":237256,"journal":{"name":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125721281","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

Joint speech/audio coding based scalable perceptual audio coding 基于可伸缩感知音频编码的语音/音频联合编码

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-04 DOI: 10.1109/ICIS.2014.6912172

Li Gao, R. Hu, Yuhong Yang

引用次数: 1

GPU-in-Hadoop: Enabling MapReduce across distributed heterogeneous platforms GPU-in-Hadoop:支持跨分布式异构平台的MapReduce

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-01 DOI: 10.1109/ICIS.2014.6912154

Jie Zhu, Juanjuan Li, Erikson Hardesty, Hai Jiang, Kuan-Ching Li

{"title":"GPU-in-Hadoop: Enabling MapReduce across distributed heterogeneous platforms","authors":"Jie Zhu, Juanjuan Li, Erikson Hardesty, Hai Jiang, Kuan-Ching Li","doi":"10.1109/ICIS.2014.6912154","DOIUrl":"https://doi.org/10.1109/ICIS.2014.6912154","url":null,"abstract":"As the size of high performance applications increases, four major challenges including heterogeneity, programmability, failure resilience, and energy efficiency have arisen in the underlying distributed systems. To tackle with all of them without sacrificing performance, traditional approaches in resource utilization, task scheduling and programming paradigm should be reconsidered. As Hadoop has handled data-intensive applications well in Clouds, GPU has demonstrated its acceleration effectiveness for computation-intensive ones. This paper intends to integrate Hadoop with CUDA to exploit both CPU and GPU resources. Hadoop will schedule MapReduce's Map and Reduce functions across multiple nodes, whereas CUDA code helps accelerate them further on local GPUs. All available heterogeneous computational power will be utilized. MapReduce in Hadoop will ease the programming task by hiding communication details. Hadoop Distributed File System will help achieve data-level fault resilience. GPU's energy efficiency characteristics help reduce the power consumption of the whole system. To achieve Hadoop and GPU integration, four approaches including Jcuda, JNI, Hadoop Streaming, and Hadoop Pipes, have been accomplished. Experimental results have demonstrated their effectiveness.","PeriodicalId":237256,"journal":{"name":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124145384","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: 26

Automatically generating abstract paintings in Malevich Style 自动生成抽象绘画在马列维奇风格

2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS) Pub Date : 2014-06-01 DOI: 10.1109/ICIS.2014.6912134

Wenyuan Tao, Yaxuan Liu, Kang Zhang

引用次数: 15