The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE)最新文献_第3页

Solving unbalanced data for Thai sentiment analysis 解决泰国情绪分析的不平衡数据

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567345

Warunya Wunnasri, T. Theeramunkong, C. Haruechaiyasak

引用次数: 5

Text mining wikipedia to discover alternative destinations 文本挖掘维基百科发现替代目的地

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567317

K. Cosh

引用次数: 2

Classification model with subspace data-dependent balls 具有子空间数据依赖球的分类模型

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567347

Nattapon Klakhaeng, Thanapat Kangkachit, T. Rakthanmanon, Kitsana Waiyamai

引用次数: 0

Evaluating software quality in use using user reviews mining 利用用户评论挖掘来评估使用中的软件质量

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567355

Warit Leopairote, A. Surarerks, N. Prompoon

{"title":"Evaluating software quality in use using user reviews mining","authors":"Warit Leopairote, A. Surarerks, N. Prompoon","doi":"10.1109/JCSSE.2013.6567355","DOIUrl":"https://doi.org/10.1109/JCSSE.2013.6567355","url":null,"abstract":"Reviews of software from experienced users play an important role for software acquisition decision. In order to share their experiences, an online software recommendation system has been developed. This information is not only useful for users or customers, but it is also be used for evaluating the software. Since there are many of reviews are accumulated and expressed in both formal and informal written languages, it takes time for concluding the evaluation. Therefore, we are interested in an automatically process to extract software information attributes from the reviews in order to provide software review representation. One essential problem is the different sentiment of the same sentence in different environment. To solve this problem, rule-based classification is used as our machine learning model. In this research, software quality extracted from user perspective with respect to ISO 9126 is selected to be the characteristic model. We also propose a methodology for a software product reviews mining based on software quality ontology and a product software quality in use scores for software review representation. Our classification approach is applied from two lists of sentiment words (positive and negative words) combining with rule-based classification method. Our result yields four percent of the accuracy improvement from simple classification applied only two lists of sentiment words.","PeriodicalId":199516,"journal":{"name":"The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121966350","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: 19

Pruning algorithm for Multi-objective optimization 多目标优化的剪枝算法

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567322

S. Sudeng, N. Wattanapongsakorn

{"title":"Pruning algorithm for Multi-objective optimization","authors":"S. Sudeng, N. Wattanapongsakorn","doi":"10.1109/JCSSE.2013.6567322","DOIUrl":"https://doi.org/10.1109/JCSSE.2013.6567322","url":null,"abstract":"Because of non-existence of an ideal single solution in Multi-objective optimization frameworks, the set of optimal solutions is required to be well spread and uniformly covering wide area of Pareto front. The decision maker (DM) still work hard to compromise the trade-offs solutions based on his/her preferences. In this paper, we proposed a pruning algorithm that can filter out undesired solutions and provides more robust trade-offs solutions to the DM. Our algorithm is called adaptive angle based pruning algorithm with bias intensity tuning (ADA). The pruning rationale is increasing the dominated area for the purpose of removing solutions that only marginally improves in some objectives while being significantly worse in other objectives. The extra angles are expanded from the regular dominated area. The bias intensity parameter (W) is introduced in order to approximate the portions of desirable solutions based on DM's opinions. We chose several benchmark problems with different difficulties including two and three objectives problems. The experimental result has shown that our pruning algorithm provides robust sub-set of Pareto-optimal solutions on several benchmark problems. The pruned Pareto-optimal solutions distributed and covered multiple regions instead of single region of Pareto front. In addition, it's clearly shown in bi-objective problems that the pruned Pareto-optimal solutions are located at knee regions of the Pareto front.","PeriodicalId":199516,"journal":{"name":"The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131204192","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: 1

A centralized management framework of network-based Intrusion Detection and Prevention System 基于网络的入侵检测与防御系统的集中管理框架

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567342

E. Wonghirunsombat, Teewalee Asawaniwed, V. Hanchana, N. Wattanapongsakorn, S. Srakaew, C. Charnsripinyo

{"title":"A centralized management framework of network-based Intrusion Detection and Prevention System","authors":"E. Wonghirunsombat, Teewalee Asawaniwed, V. Hanchana, N. Wattanapongsakorn, S. Srakaew, C. Charnsripinyo","doi":"10.1109/JCSSE.2013.6567342","DOIUrl":"https://doi.org/10.1109/JCSSE.2013.6567342","url":null,"abstract":"Many network attacks on the internet such as Denial of Service, Port Scanning, and Internet Worm can cause a lot of problems to a network system and tend to be more severe. Therefore, awareness of internet attacks is important. In this paper, we propose a centralized management framework of network-based Intrusion Detection and Prevention System (IDPS) via web application, which allows the network administrator to remotely and efficiently manage the smultiple network-based IDPSsecurity of network system. In our new framework design, multiple network-based IDPSs can be placed in various locations to inspect internet packets in the network. Each IDPS can be easily managed from anywhere and anytime by using a personal computer or a mobile device through a web browser. The web-based management system allows the network administrator to remotely monitor and handle security issues such as managing network port and IP address, updating new network information to identify new malware attacks, as well as displaying the system performance and result analysis. In addition, our network-based IDPS approach can efficiently detect network attacks and internet worms within a short time (i.e., within 2-3 seconds). Several well-known machine learning algorithms can be applied as traffic classification technique in our IDPS approach. From experimental results, we found that our network-based IDPS can analyze internet traffic which include normal packets and malware packets with high accuracy (more than 99%) as well as can immediately protect the network after intrusion detection.","PeriodicalId":199516,"journal":{"name":"The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123703884","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: 8

Interactive query suggestion in Thai library automation system 泰国图书馆自动化系统中的交互式查询建议

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567323

Warin Narawit, Siripinyo Chantamunee, Salin Boonbrahm

引用次数: 3

Emotion classification using minimal EEG channels and frequency bands 基于最小脑电信号通道和频带的情绪分类

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567313

N. Jatupaiboon, S. Pan-Ngum, P. Israsena

引用次数: 121

Inbound tourists segmentation with combined algorithms using K-Means and Decision Tree 基于k均值和决策树的入境游客分割

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567343

Wirot Yotsawat, A. Srivihok

{"title":"Inbound tourists segmentation with combined algorithms using K-Means and Decision Tree","authors":"Wirot Yotsawat, A. Srivihok","doi":"10.1109/JCSSE.2013.6567343","DOIUrl":"https://doi.org/10.1109/JCSSE.2013.6567343","url":null,"abstract":"Tourism is one of the main industries which bring about monetary to its country. To survive in the competitive industries these tourism organizations must have innovative strategies to carry on their business. One of the tools is tourism market segmentation which is used for strategic planning. This study presents inbound tourist market segmentation with combined algorithms using K-Means and Decision Tree. The study was divided into two phases. In the clustering phase, the segmentation was performed by Self Organizing Map (SOM) and K-Means. SOM used for determining the appropriate number of cluster. Then, K-Means used for refined the tourist clusters. The results of clustering phase were analyzed. In the classification phase, three classifiers were compared the performances of predictability by using the output provided by K-Means, i.e. Decision Tree, NaYve Bayes and Multilayer Perceptron (MLP). The experimental results indicated that SOM provided 6 clusters and K-Means gave better performance than SOM guided by Silhouette, Root Means Square Standard Deviation (RMSSTD) and R Square (RS). The predictive ability of J48 Decision Tree outperformed both of MLP and NaYve Bayes based on the tourist variables. J48 Decision Tree indicated the accuracy as 99.54%. The results of this study can be used for tourism management products and services.","PeriodicalId":199516,"journal":{"name":"The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"1991 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125515252","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

Adaptive multi-hop routing for wireless sensor networks 无线传感器网络的自适应多跳路由

The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2013-05-29 DOI: 10.1109/JCSSE.2013.6567328

S. Tanessakulwattana, C. Pornavalai, G. Chakraborty

{"title":"Adaptive multi-hop routing for wireless sensor networks","authors":"S. Tanessakulwattana, C. Pornavalai, G. Chakraborty","doi":"10.1109/JCSSE.2013.6567328","DOIUrl":"https://doi.org/10.1109/JCSSE.2013.6567328","url":null,"abstract":"A large portion of energy-aware routing protocol for wireless sensor networks are cluster-based. In cluster based approach, energy at the cluster head nodes are drained more rapidly compared to other member nodes. Dynamically change cluster heads periodically could partialy mitigate this problem, but clusters that are far from base station still suffer from large amount of energy for directly transmit their cluster data back to base station. Multi-hop routing was introduced to reduce energy dissipation of cluster heads that far away from base station by relaying data through nearer cluster heads. However it may overload cluster heads that are near the base station. In this paper, we propose an adaptive multi-hop hierarchical routing approach where member nodes in cluster may send their data, based on distance information, to cluster head or to base station directly to reduce energy dissipation of cluster heads. This decision is independent at each node which makes this approach highly distributed. Simulation results show that the proposed routing protocol has longer node lifetime than the original LEACH and M-LEACH protocol.","PeriodicalId":199516,"journal":{"name":"The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129213907","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