2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)最新文献_第3页

A personalized music recommender service based on Fuzzy Inference System 基于模糊推理系统的个性化音乐推荐服务

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550757

Md. Saidur Rahman, Md Saifur Rahman, S. Chowdhury, Ashfaq Mahmood, R. Rahman

引用次数: 6

Frequency-specific alterations of functional hub in generalized tonic-clonic seizure 全身性强直阵挛发作中功能中枢的频率特异性改变

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550940

Zhe Zhang, Huiyan Cheng, Xuhui Chen, Chaolin Ma

引用次数: 1

Method for classifying usability qualities and problems for action games from user reviews using text mining 基于文本挖掘的动作游戏可用性质量和问题分类方法

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550748

Artinat Wattanaburanon, N. Prompoon

{"title":"Method for classifying usability qualities and problems for action games from user reviews using text mining","authors":"Artinat Wattanaburanon, N. Prompoon","doi":"10.1109/ICIS.2016.7550748","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550748","url":null,"abstract":"Game reviewing is one of the method for game users and critics to comment and discuss about a game. Game developers and marketers could use game reviews as insights to assist on designing a better game by specifying quality requirements and providing better game marketing. Usability and problems are major concerns of users and game developers since these quality affects users' satisfaction and opportunity to increase market share respectively. However, manually extracting game usability qualities and problems from a large number of game reviews is challenging since most reviews often use natural language and may not be well-organized. This research presents a method for extracting and classifying game usability qualities and problems from game reviews using text mining technique. This research is composed of 2 main phases. The first phase is specifying game usability qualities and problems categories which also included keyword corpus creation for each category. The second phase is gathering, extracting, analyzing and classifying game reviews. The gathered game reviews will be extracted and classified into each usability qualities and problems category. Game usability qualities classification will also include sentiment classification to further specify positivity and negativity of each sentence. Accuracy metric will be used for classification evaluation. In addition, a game review summary on usability qualities and problems will be created for developers to improve game quality.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127095667","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

Local revitalization model based on soft systems methodology 基于软系统方法论的地方振兴模型

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550894

M. Iwashita, S. Kato

引用次数: 3

Supplementing Object-Oriented software change impact analysis with fault-proneness prediction 用错误倾向预测补充面向对象的软件变更影响分析

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550833

Bassey Isong, Ifeoma U. Ohaeri, M. Mbodila

{"title":"Supplementing Object-Oriented software change impact analysis with fault-proneness prediction","authors":"Bassey Isong, Ifeoma U. Ohaeri, M. Mbodila","doi":"10.1109/ICIS.2016.7550833","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550833","url":null,"abstract":"Software changes are inevitable during maintenance, Object-oriented software (OOS) in particular. For change not to be performed in the “dark”, software change impact analysis (SCIA) is used. However, due to the exponential growth in the size and complexity of OOS, classes are not without faults and the existing SCIA techniques only predict change impact set. This means that a change implemented on a faulty class could increase the likelihood for software failure. To avoid this issue, maintenance has to incorporate both change impact and fault-proneness (FP) prediction. Therefore, this paper proposes an extended approach for SCIA that integrates both activities. The goal is to assist software engineers with the necessary information of focusing verification and validation activities on the high risk components that would probably cause severe failures which in turn can boost maintenance and testing efficiency. This study built a model for predicting FP using software metrics and faults data from NASA data set in the public domain. The results obtained were analyzed and presented. Additionally, a class change recommender (CCRecommender) tool was developed to assist in computing the risks associated with making change to any component in the impact set.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000719","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

Implementation and evaluation of BLE proximity detection mechanism for Pass-by Framework 旁路框架中BLE接近检测机制的实现与评价

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550872

Ryoma Tabata, Arisa Hayashi, S. Tokunaga, S. Saiki, Masahide Nakamura, S. Matsumoto

引用次数: 7

Gaits classification of normal vs. patients by wireless gait sensor and Support Vector Machine (SVM) classifier 基于无线步态传感器和支持向量机分类器的正常与患者步态分类

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.4018/IJSI.2017010102

Taro Nakano, B. T. Nukala, J. Tsay, S. Zupancic, Amanda Rodriguez, D. Lie, Jerry Lopez, Tam Q. Nguyen

{"title":"Gaits classification of normal vs. patients by wireless gait sensor and Support Vector Machine (SVM) classifier","authors":"Taro Nakano, B. T. Nukala, J. Tsay, S. Zupancic, Amanda Rodriguez, D. Lie, Jerry Lopez, Tam Q. Nguyen","doi":"10.4018/IJSI.2017010102","DOIUrl":"https://doi.org/10.4018/IJSI.2017010102","url":null,"abstract":"Due to the serious concerns of fall risks for patients with balance disorders, it is desirable to be able to objectively identify these patients in real-time dynamic gait testing using inexpensive wearable sensors. In this work, we took a total of 49 gait tests from 7 human subjects (3 normal subjects and 4 patients), where each person performed 7 Dynamic Gait Index (DGI) tests by wearing a wireless gait sensor on the T4 thoracic vertebra. The raw gait data is wirelessly transmitted to a near-by PC for real-time gait data collection. To objectively identify the patients from the gait data, we used 4 different types of Support Vector Machine (SVM) classifiers based on the 6 features extracted from the raw gait data: Linear SVM, Quadratic SVM, Cubic SVM, and Gaussian SVM. The Linear SVM, Quadratic SVM and Cubic SVM all achieved impressive 98% classification accuracy, with 95.2% sensitivity and 100% specificity in this work. However, the Gaussian SVM classifier only achieved 87.8% accuracy, 71.7% sensitivity, and 100% specificity. The results obtained with this small number of human subjects indicates that in the near future, we should be able to objectively identify balance-disorder patients from normal subjects during real-time dynamic gaits testing using intelligent SVM classifiers.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128103584","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

Adaptive food suggestion engine by fuzzy logic 基于模糊逻辑的自适应食物建议引擎

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550755

Tousif Osman, Maisha Mahjabeen, Shahreen Shahjahan Psyche, A. Urmi, J. M. S. Ferdous, R. Rahman

引用次数: 4

Observing the evolution of social network on Weibo by sampled data 通过采样数据观察微博社交网络的演变

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550800

Lu Ma, Gang Lu, Junxia Guo

引用次数: 0

Research on software reliability evaluation technology based on BP neural network 基于BP神经网络的软件可靠性评估技术研究

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS) Pub Date : 2016-06-26 DOI: 10.1109/ICIS.2016.7550924

Lu Liu, Zhengtao Jiang

引用次数: 4