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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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KIISE Transactions on Computing Practices
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Journal DOI :
Korean Institute of Information Scientists and Engineers
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Volume & Issues
Volume 22, Issue 9 - Sep 2016
Volume 22, Issue 8 - Aug 2016
Volume 22, Issue 7 - Jul 2016
Volume 22, Issue 6 - Jun 2016
Volume 22, Issue 5 - May 2016
Volume 22, Issue 4 - Apr 2016
Volume 22, Issue 3 - Mar 2016
Volume 22, Issue 2 - Feb 2016
Volume 22, Issue 1 - Jan 2016
Selecting the target year
Compression Methods for Time Series Data using Discrete Cosine Transform with Varying Sample Size
Moon, Byeongsun ; Choi, Myungwhan ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 201~208
DOI : 10.5626/KTCP.2016.22.5.201
Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.
System Design for Analysis and Evaluation of E-commerce Products Using Review Sentiment Word Analysis
Choi, Jieun ; Ryu, Hyejin ; Yu, Dabeen ; Kim, Nara ; Kim, Yoonhee ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 209~217
DOI : 10.5626/KTCP.2016.22.5.209
As smartphone usage increases, the number of consumers who refer to review data of e-commercial products using web sites and SNS is also explosively multiplying. However, reading review data using traditional websites and SNS is time consuming. Also, it is impossible for consumers to read all the reviews. Therefore, a system that collects review data of products and conducts sentiment word analysis of the review is required to provide useful information. The majority of systems that provide such information inadequately reflect the properties of the product. In this study, we described a system that provides analysis and evaluation of e-commerce products through review sentiment words as reflected properties of the product. Furthermore, the system enables consumers to access processed information about reviews quickly and in visual format.
Automatic Scoring System for Korean Short Answers by Student Answer Analysis and Answer Template Construction
Kang, SeungShik ; Jang, EunSeo ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 218~224
DOI : 10.5626/KTCP.2016.22.5.218
This paper proposes a computer-based practical automatic scoring system for Korean short answers through student answer analysis and natural language processing techniques. The proposed system reduces the overall scoring time and budget, while improving the ease-of-use to write answer templates from student answers as well as the accuracy and reliability of automatic scoring system. To evaluate the application of the automatic scoring system and compare to the human scoring process, we performed an experiment using the student answers of social science subject in 2014 National Assessment of Educational Achievement.
A Health Assessment Platform with IoT Devices
La, Hyun Jung ; Kim, Moon Kwon ; Kim, Soo Dong ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 225~234
DOI : 10.5626/KTCP.2016.22.5.225
The emergence of diverse medical Internet of Things (IoT) devices has facilitated the collection and analysis of medical contexts to assess health conditions. However, the complexity of IoT-based systems for health assessment is quiet high and it requires high development cost, since the designs of the systems highly depend on the heath aspects to be evaluated. In this paper, we propose a design of the platform that provides generic functionalities to various health evaluation applications. We first define a metric for computing a health index, which is a generic health assessment model. And, based on the proposed generic health index, we propose a design of the platform to evaluate diverse aspects of the health including its hardware architecture, software architecture and database design. We describe the result of developing Rainbow Toilet System based on the proposed platform, and assess the practical applicability.
A Technique to Link Bug and Commit Report based on Commit History
Chae, Youngjae ; Lee, Eunjoo ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 235~239
DOI : 10.5626/KTCP.2016.22.5.235
'Commit-bug link', the link between commit history and bug reports, is used for software maintenance and defect prediction in bug tracking systems. Previous studies have shown that the links are automatically detected based on text similarity, time interval, and keyword. Existing approaches depend on the quality of commit history and could thus miss several links. In this paper, we proposed a technique to link commit and bug report using not only messages of commit history, but also the similarity of files in the commit history coupled with bug reports. The experimental results demonstrated the applicability of the suggested approach.
Sentiment Analysis using Latent Structural SVM
Yang, Seung-Won ; Lee, Changki ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 240~245
DOI : 10.5626/KTCP.2016.22.5.240
In this study, comments on restaurants, movies, and mobile devices, as well as tweet messages regardless of specific domains were analyzed for sentimental information content. We proposed a system for extraction of objects (or aspects) and opinion words from each sentence and the subsequent evaluation. For the sentiment analysis, we conducted a comparative evaluation between the Structural SVM algorithm and the Latent Structural SVM. As a result, the latter showed better performance and was able to extract objects/aspects and opinion words using VP/NP analyzed by the dependency parser tree. Lastly, we also developed and evaluated the sentiment detector model for use in practical services.
Associated Keyword Recommendation System for Keyword-based Blog Marketing
Choi, Sung-Ja ; Son, Min-Young ; Kim, Young-Hak ;
KIISE Transactions on Computing Practices, volume 22, issue 5, 2016, Pages 246~251
DOI : 10.5626/KTCP.2016.22.5.246
Recently, the influence of SNS and online media is rapidly growing with a consequent increase in the interest of marketing using these tools. Blog marketing can increase the ripple effect and information delivery in marketing at low cost by prioritizing keyword search results of influential portal sites. However, because of the tough competition to gain top ranking of search results of specific keywords, long-term and proactive efforts are needed. Therefore, we propose a new method that recommends associated keyword groups with the possibility of higher exposure of the blog. The proposed method first collects the documents of blog including search results of target keyword, and extracts and filters keyword with higher association considering the frequency and location information of the word. Next, each associated keyword is compared to target keyword, and then associated keyword group with the possibility of higher exposure is recommended considering the information such as their association, search amount of associated keyword per month, the number of blogs including in search result, and average writhing date of blogs. The experiment result shows that the proposed method recommends keyword group with higher association.