2013 International Computer Science and Engineering Conference (ICSEC)最新文献_第2页

Prediction of stock price using an adaptive Neuro-Fuzzy Inference System trained by Firefly Algorithm 用萤火虫算法训练的自适应神经模糊推理系统预测股票价格

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694798

Hien Nguyen Nhu, S. Nitsuwat, M. Sodanil

引用次数: 35

Detecting Romanized Thai tokens in social media texts 在社交媒体文本中检测罗马化泰国符号

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694753

Nutthamon Moknarong, A. Suchato, P. Punyabukkana

{"title":"Detecting Romanized Thai tokens in social media texts","authors":"Nutthamon Moknarong, A. Suchato, P. Punyabukkana","doi":"10.1109/ICSEC.2013.6694753","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694753","url":null,"abstract":"Social media contents were created by a large number of users or writers. Additionally, each of them has their own writing styles, which depend on their creative thinking or attitudes. As commonly found in online social networks of Thai users, typed texts sometimes include Thai words that were transliterated with Roman letters. Therefore, text-to-speech systems cannot pronounce these transliterated tokens correctly. In this work, we propose and evaluate statistical methods for detecting Romanized Thai tokens. Both context-dependent and context-free classification features are proposed. Real social network texts are used for constructing the training set and the test set. Human subjects can detect Thai Romanized tokens at 91.16% accuracy on average when adjacent contexts are hidden while the accuracy is at 99.41% with contexts. With the proposed features, a decision tree-based classifier and an N-gram-based classifier yield 87.63% and 74.42% accuracy, respectively. In the later case, the accuracy increases to 82.60% when the tokens' existence in English dictionaries is considered. Combining the two methods results in a detection accuracy of 89.36%.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123946156","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

Buddhist amulet coin recognition by genetic algorithm 基于遗传算法的佛教护身符硬币识别

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694802

C. Pornpanomchai, Natdanai Srisupornwattana

引用次数: 4

Efficient evolution-based clustering of high dimensional data streams with dimension projection 基于维投影的高维数据流高效进化聚类

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694776

Rattanapong Chairukwattana, Thanapat Kangkachit, T. Rakthanmanon, Kitsana Waiyamai

{"title":"Efficient evolution-based clustering of high dimensional data streams with dimension projection","authors":"Rattanapong Chairukwattana, Thanapat Kangkachit, T. Rakthanmanon, Kitsana Waiyamai","doi":"10.1109/ICSEC.2013.6694776","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694776","url":null,"abstract":"SE-Stream is an evolution-based stream clustering method that supports high dimensional data streams. SE-Stream is able to monitor and detect change in the clustering structure during the progression of data streams. In this paper, we improve performance of SE-Stream by reducing its execution time and increasing its cluster quality. SE-Stream reduces complexity of stream processing by determining appropriated subset of dimensions of each active cluster to express cluster specific characteristics during the progression of data streams. With elimination of redundant operations, SE-Stream is improved both in terms of cluster quality and execution time. Experimental results on two real-world datasets show that SE-Stream outperforms its previous version in terms execution time. Further, the cluster quality in terms of both purity and f-measure has been considerably improved. Compared with HPStream, a state of the art algorithm for projected clustering of high dimensional data streams, SE-Stream outperforms in terms of cluster quality and yields comparable execution time.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116041557","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

Support Vector Machine accuracy improvement with k-means clustering 基于k-means聚类的支持向量机精度改进

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694782

Teera Siriteerakul, V. Boonjing

{"title":"Support Vector Machine accuracy improvement with k-means clustering","authors":"Teera Siriteerakul, V. Boonjing","doi":"10.1109/ICSEC.2013.6694782","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694782","url":null,"abstract":"Support Vector Machine (SVM) is a classifier tool which, originally, uses a hyperplane as a border for separating two classes of data in hyperspace. However, if data from each class are not clustered together, the two classes might not be linearly separable. Typically, researchers attempted to resolve this issue by replacing the hyperplane with a complex border via kernel tricks. However, these kernel tricks could result in a longer training time or only a minute accuracy improvement (or both). On the other hand, if data from one class are separated into subclasses according to their proximity, then all the subclasses should be easily separated by hyperplanes. Therefore, this paper proposes a method to improve the accuracy of linear SVM by first applying k means clustering to each class of input data. Then, after clustered, a multi-classes linear SVM is trained using each subclass as a separate class. Thus, the trained SVM can identify any new input into a subclass which can be easily mapped to the correct class. To evaluate, the proposed method is experimentally used to classify images of Thai character where multiple fonts of characters can be taken as hidden clusters within classes. Empirically, the proposed method could achieve over 6% improvement from a linear SVM or SVMs with RBF or polynomial kernel.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122370738","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

Improving the running time of the nearest neighbor algorithm 改进了最近邻算法的运行时间

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694795

Nattakon Chompupatipong, K. Jearanaitanakij

引用次数: 0

Ontology development for SMEs E-commerce website based on content analysis and its recommendation system 基于内容分析的中小企业电子商务网站本体开发及其推荐系统

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694744

Pagon Gatchalee, Zhoujun Li, T. Supnithi

引用次数: 4

Path-reputation based technique in reactive AODV Ad Hoc sensor networks routing for flood warning application 基于路径声誉的响应式AODV Ad Hoc传感器网络洪水预警路由技术

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694790

Nuttida Khawsaard, C. Saivichit

引用次数: 0

The last eternity a 3D role-playing game with a cross-platform development 最后的永恒是一款跨平台开发的3D角色扮演游戏

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694800

Yodthong Rodkaew

引用次数: 6

A performance evaluation of a probabilistic parallel genetic algorithm: FPGA vs. multi-core processor 概率并行遗传算法的性能评估:FPGA与多核处理器

2013 International Computer Science and Engineering Conference (ICSEC) Pub Date : 2013-09-01 DOI: 10.1109/ICSEC.2013.6694797

Y. Jewajinda

引用次数: 3