2016 8th International Conference on Knowledge and Smart Technology (KST)最新文献

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Paragraph2Vec-based sentiment analysis on social media for business in Thailand 基于泰国社交媒体的商业情感分析
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-02-01 DOI: 10.1109/KST.2016.7440526
P. Sanguansat
{"title":"Paragraph2Vec-based sentiment analysis on social media for business in Thailand","authors":"P. Sanguansat","doi":"10.1109/KST.2016.7440526","DOIUrl":"https://doi.org/10.1109/KST.2016.7440526","url":null,"abstract":"This paper proposes the sentiment analysis system in Thai language. It aims to use for the three business types (Retail, Banking and Telecommunication) to monitor their brand image via social media. Pantip.com is the most popular online community in Thailand, which many customers posted the comments about their business. Normally, three sentiments must be identified (positive, negative and neutral), but four sentiments (positive, negative, neutral and need) are introduced in our proposed system because the need sentiment can be used for generating new business opportunities. The unsupervised deep learning feature extraction for text, called Paragraph2Vec, paragraph vector or Doc2Vec, was applied in this paper, compared to the classical TF-IDF. The experimental results show that our proposed method perform better than the baseline method.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134133018","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: 21
Fast and accurate template averaging for time series classification 快速准确的模板平均时间序列分类
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-02-01 DOI: 10.1109/KST.2016.7440530
Phongsakorn Sathianwiriyakhun, Thapanan Janyalikit, C. Ratanamahatana
{"title":"Fast and accurate template averaging for time series classification","authors":"Phongsakorn Sathianwiriyakhun, Thapanan Janyalikit, C. Ratanamahatana","doi":"10.1109/KST.2016.7440530","DOIUrl":"https://doi.org/10.1109/KST.2016.7440530","url":null,"abstract":"Time series data are evidently ubiquitous, as we could see them in all kinds of domains and applications. As a result, various data mining tasks are often performed to discover useful knowledge, including commonly performed tasks like time series classification and clustering. Dynamic Time Warping (DTW) is accepted as one of the best available similarity measures, which has been used for distance calculation in both classification and clustering algorithms. However, its known drawback is its exceedingly high computational cost. Recently, data condensation method through template averaging is applied; each class of data can be represented by one template which could greatly speed up the classification with DTW especially in large datasets, with the trade off in lower classification accuracies. Subsequently, various attempts have been made to increase the number of representative templates to boost up the accuracies while keeping the computation complexity not too high. However, those algorithms still suffer from many predefined and hard-to-set parameters, while some require high computation time for high accuracy results. Therefore, in this work, we propose an accurate yet simple template averaging method that is parameter free and has much less computation time. The experiment results on 20 UCR time series benchmark datasets demonstrate that our proposed method can achieve a few orders of magnitude speedup while maintaining high classification accuracies.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130685915","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: 18
Building a granular knowledge monitor: An application of the A.U.R.A framework 构建一个粒度知识监视器:A.U.R.A框架的一个应用程序
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-02-01 DOI: 10.1109/KST.2016.7440481
Alexander Denzler, Marcel Wehrle, Andreas Meier
{"title":"Building a granular knowledge monitor: An application of the A.U.R.A framework","authors":"Alexander Denzler, Marcel Wehrle, Andreas Meier","doi":"10.1109/KST.2016.7440481","DOIUrl":"https://doi.org/10.1109/KST.2016.7440481","url":null,"abstract":"Gaining the ability to identify, assess and display what knowledge a user holds, especially in a digital environment that is designed to facilitate it's exchange, is of great value. In this paper the authors will present a newly designed framework for this task and a prototype to demonstrate it's applicability. The introduced framework will be able to cope with different data types, as well as explicitly and implicitly provided information. Furthermore, is being ensured that the various characteristics of knowledge, such as vagueness, imprecision and abstraction are accounted for. The developed prototype is presented in the final section of this paper.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133565153","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
Optimal buffer allocation and service rates in flow line production system 流水线生产系统中缓冲器的最优分配和服务率
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-02-01 DOI: 10.1109/KST.2016.7440477
S. Horng, Shieh-Shing Lin
{"title":"Optimal buffer allocation and service rates in flow line production system","authors":"S. Horng, Shieh-Shing Lin","doi":"10.1109/KST.2016.7440477","DOIUrl":"https://doi.org/10.1109/KST.2016.7440477","url":null,"abstract":"In this research, we present a method to solve for an optimal solution vector containing buffer allocation and service rates of the flow line production (FLP) system such that the throughput is maximized. The solution method integrates the elitist teaching-learning-based optimization (ETLBO) and optimal computing budget allocation (OCBA). At first, The FLP system is formulated as an integer-valued inequality constrained optimization problem with a large search space. The ETLBO is then utilized to select N excellent solutions from the search space, where the objective value is evaluated with the radial basis function (RBF). The RBF is taken as a meta-model to approximately estimate the objective value of a solution vector. Lastly, the OCBA scheme is adopted to look for an optimal solution vector. The solution method is tested on two examples of FLP system, one comprising 3-stage and another comprising 12-stage. Simulation results present that the superiority of the solution method in the solution quality and computing efficiency using extensive simulations.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133441892","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
Semantic anonymization in publishing categorical sensitive attributes 发布分类敏感属性的语义匿名化
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-02-01 DOI: 10.1109/KST.2016.7440495
A. A. Mubark, Emad Elabd, Hatem M. Abdelkader
{"title":"Semantic anonymization in publishing categorical sensitive attributes","authors":"A. A. Mubark, Emad Elabd, Hatem M. Abdelkader","doi":"10.1109/KST.2016.7440495","DOIUrl":"https://doi.org/10.1109/KST.2016.7440495","url":null,"abstract":"The need of improving the privacy on data publisher becomes more important because data grows very fast. Traditional methods for privacy preserving data publishing cannot prevent privacy leakage. This causes the continuous research to find better methods to prevent privacy leakage. K-anonymity and L-diversity are well-known techniques for data privacy preserving. These techniques cannot prevent the similarity attack on the data privacy because they did not take into consider the semantic relation between the sensitive attributes of the categorical data. In this paper, we proposed an approach to categorical data preservation based on Domain-based of semantic rules to overcome the similarity attacks. The experimental results of the proposal approach focused to categorical data presented. The results showed that the semantic anonymization increases the privacy level with effect data utility.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116935809","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
Face recognition using string grammar fuzzy K-nearest neighbor 人脸识别使用字符串语法模糊k近邻
2016 8th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2016-02-01 DOI: 10.1109/KST.2016.7440531
Payungsak Kasemsumran, S. Auephanwiriyakul, N. Theera-Umpon
{"title":"Face recognition using string grammar fuzzy K-nearest neighbor","authors":"Payungsak Kasemsumran, S. Auephanwiriyakul, N. Theera-Umpon","doi":"10.1109/KST.2016.7440531","DOIUrl":"https://doi.org/10.1109/KST.2016.7440531","url":null,"abstract":"A string grammar fuzzy K-nearest neighbor is developed by incorporating 2 types of membership value into string grammar K-nearest neighbor. We apply these two string grammar fuzzy K-nearest neighbors in the face recognition system. The system provides 99.25%, 99.75%, 79.57%, 93.85%, and 100% in ORL, MIT-CBCL, Georgia Tech, FEI and JAFFE databases, respectively. Although, the results are satisfied, there are some limitations on the system. It is not scale-invariant. Also, the Levenshtein distance might create misperception between strings that are actually far apart but the calculated distance is small.","PeriodicalId":350687,"journal":{"name":"2016 8th International Conference on Knowledge and Smart Technology (KST)","volume":"5 Spec No 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128575727","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: 14
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