2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)最新文献

The Research of Several Situations About Memory Accessing on Non-Uniform Memory Access Architecture 非统一存储器访问体系结构中存储器访问的几种情况研究

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466393

Xiaomei Guo, Haiyun Han

引用次数: 0

Pricing Models for Crowdsourcing Tasks Based on Geographic Information 基于地理信息的众包任务定价模型

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466433

Yuxin Niu, Yingtao Zhang, M. Song

引用次数: 3

Reverse-Learning Particle Swarm Optimization Algorithm Based on Niching Technology 基于小生境技术的逆向学习粒子群优化算法

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466391

Hongbin Dong, Hua Zhang, Shuang Han, Xiaohui Li, Xiaowei Wang

引用次数: 4

Enhanced Ant Colony Optimization with Local Search 基于局部搜索的增强蚁群优化

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466388

Yindee Oonsrikaw, A. Thammano

引用次数: 5

New Words Discovery Method Based On Word Segmentation Result 基于分词结果的新词发现方法

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466490

Heyang Liu, Pengdong Gao, Yi Xiao

{"title":"New Words Discovery Method Based On Word Segmentation Result","authors":"Heyang Liu, Pengdong Gao, Yi Xiao","doi":"10.1109/ICIS.2018.8466490","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466490","url":null,"abstract":"A kind of new words discovery method based on word segmentation result is presented in this paper. Word segmentation is an important part of many Chinese Natural language processing (NLP) tasks. Improving the accuracy of Chinese word segmentation is a matter of great concern. With the increasing number of web text, more and more Chinese NLP tasks need to use micro-blog, movie review and other web text. The content of web text changes very fast and often contains a large number of new words. It is an important factor affecting the accuracy of word segmentation that word segmentation tools can not identify these new words. One way to solve this problem is to discover new words in the text to use and add these new words to the dictionaries on which the word segmentation tool depends. The traditional method of new words discovery can only find the words that do not exist in word segmentation tool’s dictionary. But these words do not necessarily affect the result of the word segmentation. That is, the words may be correctly segmented even if they are not added to the word segmentation tool’s dictionary. To address this issue, we propose to build a collection of candidate new words based on segmentation result. All the new words discovered in this way segmented by the word segmentation tool by mistake. Adding these new words to the word segmentation tool’s dictionary can improve the accuracy of the word segmentation more than traditional methods. Experiments on the DouBan movie review dataset show that our method can get better new words to improve the accuracy on movie review sentiment classification.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"8 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":"115546405","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

Feasibility of dictionary-based sparse coding for data compression in machine condition-based monitoring 基于字典的稀疏编码在机器状态监测数据压缩中的可行性

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8671663

W. Goh, Nicholas Sadjoli

引用次数: 1

An Improved Distributed File System Based on GPU Acceleration 基于GPU加速的改进分布式文件系统

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466439

Songtao Shang, Yong Gan, Huaiguang Wu

引用次数: 0

3D Model Dynamic Perforation Simulation Based on Game Engine 基于游戏引擎的三维模型动态射孔仿真

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466541

Wenfeng Hu, Taobo Gao, Yue Li

引用次数: 0

An Analysis of Myanmar Inflectional Morphology Using Finite-state Method 缅甸语屈折形态的有限状态分析

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466526

Tin Myo Latt, A. Thida

引用次数: 1

Emotion Recognition in Elderly Based on SpO2 and Pulse Rate Signals Using Support Vector Machine 基于SpO2和脉搏率信号的老年人情绪识别

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI: 10.1109/ICIS.2018.8466489

Lutfi Hakim, A. Wibawa, Evi Septiana Pane, M. Purnomo

{"title":"Emotion Recognition in Elderly Based on SpO2 and Pulse Rate Signals Using Support Vector Machine","authors":"Lutfi Hakim, A. Wibawa, Evi Septiana Pane, M. Purnomo","doi":"10.1109/ICIS.2018.8466489","DOIUrl":"https://doi.org/10.1109/ICIS.2018.8466489","url":null,"abstract":"Emotion recognition based on physiological signal has become an important issue among researchers nowadays. It is because many studies have proven that emotion condition, especially in elderly, has influenced the physical condition significantly. Nevertheless, there are still few studies which discuss and explores emotion recognition based on SpO2 and Pulse Rate Signals. This paper proposed emotion recognition of three basic emotions of elders, such as happy, sad and angry based on those physiological signals. Window size segmentation that was used to extract both physiological signals was 15 second. Then, statistical feature extraction method was used to obtain the features of SpO2 and Pulse Rate (PR). Support Vector Machine (SVM) with selecting the best of C and γ parameters and the most optimal K parameters of k-Nearest Neighbors (k-NN) method were used to classify the extracted features which were tested in several scenarios: classification using SpO2, using PR and using SpO2–PR features. The result showed that SVM achieved the best accuracy (72.86%) and precision (71.30%) compared to k-NN. Furthermore, combining the features of both physiological signals could improve the accuracy and precision scores more than 3.70% compared to the single physiological signal. This result provides information of emotion recognition in term of SpO2 and PR signals which can be better detected by combining the features of both physiological signals. Moreover, the optimal C and γ parameters of SVM and K-value of k-NN can be implemented to achieve better classification result.","PeriodicalId":447019,"journal":{"name":"2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)","volume":"1 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":"126313345","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