2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)最新文献

International Program Committee 国际项目委员会

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-09-01 DOI: 10.1109/CCGRID.2006.149

I. Benbasat, P. Ein-Dor, John D. Johnson, Robert D. Johnston, G. Kanji, E. Sibley, F. Tan, Andrew Whinston, Philip S. Yu, Vladimir Zwass, W. Bellows, P. Berg, T. Brown, T. Bui, Houn-Gee Chen, S. Chou, C. Haugtvedt, Thomas W Jones, Seung-Chul Kim, Ching-Chyi Lee, Mei Lin, H. Lai, H. Luczak

引用次数: 0

Market Analysis as a Possible Activity of Software Project Management 市场分析作为软件项目管理的一种可能活动

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477215

Sarah Tahsin, Abdul Munim, Mahady Hasan, N. Nahar, M. Rokonuzzaman

引用次数: 5

Enhanced Sentiment Classification for Informal Myanmar Text of Restaurant Reviews 餐厅评论非正式缅甸文本的增强情感分类

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477231

Yu Mon Aye, Sint Sint Aung

{"title":"Enhanced Sentiment Classification for Informal Myanmar Text of Restaurant Reviews","authors":"Yu Mon Aye, Sint Sint Aung","doi":"10.1109/SERA.2018.8477231","DOIUrl":"https://doi.org/10.1109/SERA.2018.8477231","url":null,"abstract":"Nowadays, users' desire reviews and online blogs sites to purchase the products. With the rapid grown in social networks, the online services are gradually more being used by online society to share their sight, opinion, feelings and incident about a particular product or event. Therefore, customer reviews are considered as a significant resource of information in Sentiment Analysis (SA) applications for decision making of economic. Sentiment analysis is a language processing task which is used to detect opinion articulated in online reviews to classify it into different polarity. Most of resources for sentiment analysis are built for English than other language. To overcome this problem, we propose the sentiment analysis for Myanmar language by considering intensifier and objective words to enhance sentiment classification for food and restaurant domain. This paper aims to overcome the language specific problem and to enhance the sentiment classification for informal text. We address lexicon-based sentiment analysis to enhance the sentiment analysis for Myanmar text reviews and show that the enhancement of sentiment classification improves the prediction accuracy.","PeriodicalId":161568,"journal":{"name":"2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116478409","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: 6

Tourist Gender Differences Through Lens of Social Sensing 社会感知视角下的游客性别差异

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477201

Jun Wang, Baoguo Yu, Yunpeng Li

引用次数: 0

Service Differentiation Strategy Based on User Demands for Https Web Servers 基于用户需求的Https Web服务器服务差异化策略

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477205

Lu Yan, Haojiang Deng, Xiao Chen, Xiaozhou Ye

引用次数: 0

Dynamic Performance Aware Reduce Task Scheduling in MapReduce on Virtualized Environment 虚拟化环境下MapReduce的动态性能感知Reduce任务调度

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477195

Rathinaraja Jeyaraj, V. S. Ananthanarayana

{"title":"Dynamic Performance Aware Reduce Task Scheduling in MapReduce on Virtualized Environment","authors":"Rathinaraja Jeyaraj, V. S. Ananthanarayana","doi":"10.1109/SERA.2018.8477195","DOIUrl":"https://doi.org/10.1109/SERA.2018.8477195","url":null,"abstract":"Hadoop MapReduce as a service from cloud is widely used by various research, and commercial communities. Hadoop MapReduce is typically offered as a service hosted on virtualized environment in Cloud Data-Center. Cluster of virtual machines for MapReduce is placed across racks in Cloud Data-Center to achieve fault tolerance. But, it negatively introduces dynamic/heterogeneous performance for virtual machines due to hardware heterogeneity and co-located virtual machine's interference, which cause varying latency for same task. Alongside, curbing number of intermediate records and placing reduce tasks on right virtual node are also important to minimize MapReduce job latency further. In this paper, we introduce Multi-Level Per Node Combiner to minimize the number of intermediate records and Dynamic Ranking based MapReduce Job Scheduler to place reduce tasks on right virtual machine to minimize MapReduce job latency by exploiting dynamic performance of virtual machines. To experiment and evaluate, we launched 29 virtual machines hosted in eight different physical machines to run wordcount job on PUMA dataset. Our proposed methodology improves overall job latency up to 33% for wordcount job.","PeriodicalId":161568,"journal":{"name":"2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134507438","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: 2

Design and Implementation of High Concurrent Communication Server in Health Monitoring System 健康监测系统中高并发通信服务器的设计与实现

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477204

Junhuai Li, Yue Li, Jingfei Fu, Huaijun Wang, Lei Yu

引用次数: 0

An Overview of Event Based Directional Change for Algorithmic Trading 基于事件的算法交易方向变化概述

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477229

Botao Ye, Dejun Xie

引用次数: 1

Hybrid Intrusion Detection System Using K-Means and Classification and Regression Trees Algorithms 基于k -均值和分类回归树算法的混合入侵检测系统

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477203

Y. Y. Aung, M. Min

{"title":"Hybrid Intrusion Detection System Using K-Means and Classification and Regression Trees Algorithms","authors":"Y. Y. Aung, M. Min","doi":"10.1109/SERA.2018.8477203","DOIUrl":"https://doi.org/10.1109/SERA.2018.8477203","url":null,"abstract":"Intrusion detection is the process called indentifying invasions. The action to enter a system without permission is called intrusion. By adding advanced technologies to mobile phones, such as smart phones, tablets, smart devices, other computing devices, the number of Internet users are increasingly growing. Therefore, network security is very important for all Internet users. IDS are essential for security limits. So, now Internet consumers are considered mandatory safety devices for critical networks. There are many traditional techniques of intrusion detection. In research on traditional intrusion detection technology analysis, the statistical model for setting up rules, management and aggression capability and so on are still some disadvantages and disabilities, because the actual test results cannot meet the requirements. There are many current methods used in. Each method has advantage and disadvantage. Intrusion detection can also be considered as a classification problem. In this research we use K-means algorithm and classification and regression trees (CART) algorithm. The purpose of this paper is to show good accuracy in performance analysis with time complexity by using hybrid data mining method. This model is verified by KDD'99 data set.","PeriodicalId":161568,"journal":{"name":"2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127279068","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: 13

The Research of Multi-Label $k$-Nearest Neighbor Based on Descending Dimension 基于降维的多标签k最近邻研究

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) Pub Date : 2018-06-01 DOI: 10.1109/SERA.2018.8477210

Song Gao, Xiaodan Yang, Lihua Zhou, Shaowen Yao

{"title":"The Research of Multi-Label $k$-Nearest Neighbor Based on Descending Dimension","authors":"Song Gao, Xiaodan Yang, Lihua Zhou, Shaowen Yao","doi":"10.1109/SERA.2018.8477210","DOIUrl":"https://doi.org/10.1109/SERA.2018.8477210","url":null,"abstract":"With the in-depth research of data classification, multi-label classification has become a hot issue of research. Multi-label $boldsymbol{k}$-nearest neighbor (ML-$boldsymbol{k}$ NN) is a classification method which predicts the unclassified instances' labels by learning the classified instances. However, this method doesn't consider the interrelationships between attributes and labels. Considering the relationships between properties and labels can improve accuracy of classification methods, but the diversities of properties and labels will present the curse of dimensionality. This problem make such methods can not be expanded under the background of big data. To solve this problem, this paper proposes three methods, called multi-label $boldsymbol{k}$-nearest neighbor based on principal component analysis(PML-$boldsymbol{k}mathbf{NN}$), coupled similarity multi-label k-nearest neighbor based on principal component analysis(PCSML-$boldsymbol{k}mathbf{NN}$) and coupled similarity multi-label k-nearest neighbor classification based on feature selection (FCSML-$boldsymbol{k}mathbf{NN}$), which use feature extraction and feature selection to reduce the dimensions of labels' properties. We test the ML-$boldsymbol{k}mathbf{NN}$ and the three methods we proposed with two real data, the experimental results show that reduce the dimensions of labels' properties can improve the efficiency of classification methods.","PeriodicalId":161568,"journal":{"name":"2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"395 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122923943","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