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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartD
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Korea Information Processing Society
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Volume & Issues
Volume 18D, Issue 6 - Dec 2011
Volume 18D, Issue 5 - Oct 2011
Volume 18D, Issue 4 - Aug 2011
Volume 18D, Issue 3 - Jun 2011
Volume 18D, Issue 2 - Apr 2011
Volume 18D, Issue 1 - Feb 2011
Selecting the target year
Efficient Computation of a Skyline under Location Restrictions
Kim, Ji-Hyun ; Kim, Myung ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 313~316
DOI : 10.3745/KIPSTD.2011.18D.5.313
The skyline of a multi-dimensional data set is a subset that consists of the data that are not dominated by other members of the set. Skyline computation can be very useful for decision making for multi-dimensional data set. However, in case that the skyline is very large, it may not be much useful for decision making. In this paper, we propose an algorithm for computing a part of the skyline considering location restrictions that the user provides, such as origin movement, degree ranges and/or distances from the origin. The algorithm eliminates noncandidate data rapidly, and returns in order the skyline points that satisfy the user's requests. We show that the algorithm is efficient by experiments.
A Text-based Similarity Measure for Scientific Literature
Yoon, Seok-Ho ; Kim, Sang-Wook ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 317~322
DOI : 10.3745/KIPSTD.2011.18D.5.317
This paper addresses computing of similarity among papers using text-based measures. First, we analyze the accuracy of the similarities computed using different parts of a paper, and propose a method of Keyword-Extension, which is very useful when text information is incomplete. Via a series of experiments, we verify the effectiveness of Keyword-Extension.
Earth Mover's Distance Approximate Earth Mover's Distance for the Efficient Content-based Image Retreival
Jang, Min-Hee ; Kim, Sang-Wook ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 323~328
DOI : 10.3745/KIPSTD.2011.18D.5.323
For content-based image retrieval, the earth mover's distance and the optimal color composition distance are proposed to measure the dissimilarity. Although providing good retrieval results, both methods are too time-consuming to be used in a large image database. To solve the problem, we propose a new distance function that calculates an approximate earth mover's distance in linear time. To calculate the dissimilarity in linear time, the proposed approach employs the space-filling curve. We have performed extensive experiments to show the effectiveness and efficiency of the proposed approach. The results reveal that our approach achieves almost the same results with the EMD in linear time.
Terminology Recognition System based on Machine Learning for Scientific Document Analysis
Choi, Yun-Soo ; Song, Sa-Kwang ; Chun, Hong-Woo ; Jeong, Chang-Hoo ; Choi, Sung-Pil ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 329~338
DOI : 10.3745/KIPSTD.2011.18D.5.329
Terminology recognition system which is a preceding research for text mining, information extraction, information retrieval, semantic web, and question-answering has been intensively studied in limited range of domains, especially in bio-medical domain. We propose a domain independent terminology recognition system based on machine learning method using dictionary, syntactic features, and Web search results, since the previous works revealed limitation on applying their approaches to general domain because their resources were domain specific. We achieved F-score 80.8 and 6.5% improvement after comparing the proposed approach with the related approach, C-value, which has been widely used and is based on local domain frequencies. In the second experiment with various combinations of unithood features, the method combined with NGD(Normalized Google Distance) showed the best performance of 81.8 on F-score. We applied three machine learning methods such as Logistic regression, C4.5, and SVMs, and got the best score from the decision tree method, C4.5.
XML Document Clustering Technique by K-means algorithm through PCA
Kim, Woo-Saeng ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 339~342
DOI : 10.3745/KIPSTD.2011.18D.5.339
Recently, researches are studied in developing efficient techniques for accessing, querying, and storing XML documents which are frequently used in the Internet. In this paper, we propose a new method to cluster XML documents efficiently. We use a K-means algorithm with a Principal Component Analysis(PCA) to cluster XML documents after they are represented by vectors in the feature vector space by transferring them as names and levels of the elements of the corresponding trees. The experiment shows that our proposed method has a good result.
An automation method for GUI test using a UIA library
Choi, Chang-Min ; Chung, In-Sang ; Kim, Hyeon-Soo ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 343~356
DOI : 10.3745/KIPSTD.2011.18D.5.343
When preparing test cases and running the test the existing GUI test tools require many tester's interventions. To cope with such problem this paper suggests a new method to build test cases for GUI test. This method identifies the potential control flows within the GUI and constructs the GUI map. The UIA library in .NET Framework is used to extract information about the GUI controls and the GUI map is constructed by the extracted information. Test scenarios are generated from the extracted information about the GUI controls using the grouping mechanism. Based on the grouping mechanism, various test scenarios which are test cases in GUI tests can be made by replacing a GUI control by another one in the same group. The existing GUI test tools do not support the concept of test coverage. Since, however, our method survey which part of the GUI map is executed or not during running the test, the test coverage can be measured by using the GUI map.
A Study on Acceptance Vitalizations Plans of NEIS Parents Services Based on ANP BCR Model: Targeting Elementary School Parents
Seo, Hyun-Sik ; Song, In-Kuk ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 357~370
DOI : 10.3745/KIPSTD.2011.18D.5.357
The study aims to examine the service preference between the NEIS(National Education Information Systems) and alternatives, based on the benefits, costs and risks of NEIS service for parents, and finally propose the vitalizations plans for that public services. As a part of public services, NEIS has not only provided the educational information for the students, which enables school parents to suffice for information need, and but also leaded in the parents' participation for the various educational policies. However, major NEIS users such as teachers and parents recently began to blame for the various data errors and connection failures of NEIS. Despite of the research importance, most of NEIS studies severely depended on TAM and researches investigating the preference of school parents for NEIS services rarely exist. The study classifies NEIS parents services into benefits, costs, and risks based on ANP BCR model, identifies the preference for the services, compares the NEIS services and alternatives, and provides the results of sensitivity analyses. The analyses identify that NEIS was not frequently used by school parents and that the service preference of the school parents was not considered yet. Consequently, the study stresses the acceptance vitalizations plans for NEIS.
Design of a Logistics Decision Support System for Transportation Mode Selection considering Carbon Emission Cost
Song, Byung-Jun ; Koo, Je-Kwon ; Song, Sang-Hwa ; Lee, Jong-Yun ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 371~384
DOI : 10.3745/KIPSTD.2011.18D.5.371
This paper considers logistics decision support system which deals with transportation mode selection considering transportation and carbon emission cost. Transportation and carbon emission costs vary with the choice of transportation modes and to become competitive companies need to find proper transportation modes for their logistics services. However, due to the restricted capacity of transportation modes, it is difficult to balance transportation and carbon emission costs when designing logistics network including transportation mode choice for each service. Therefore this paper aims to analyze the trade-off relationship between transportation and carbon emission cost in mode selection of intermodal transportation and to provide optimal green logistics strategy. In this paper, the logistics decision support system is designed based on mixed integer programming model. To understand the trade-off relationship of transportation and carbon emission cost, the system is tested with various scenarios including transportation of containers between Seoul and Busan. The analysis results show that, even though sea transportation combined with trucking is competitive in carbon emission per unit distance travelled, the total cost of carbon emission and transportation for the sea transportation may not have competitive advantage over other transportation modes including rail and truck transportation modes. The sea-based intermodal logistics service may induce detours which have negative impacts on the overall carbon emission. The proposed logistics decision support system is expected to play key role in green logistics and supply chain management.
A Design of SOA-based Data Integration Framework for Effective Spatial Data Mining
Moon, Il-Hwan ; Hur, Hwan ; Kim, Sam-Keun ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 385~392
DOI : 10.3745/KIPSTD.2011.18D.5.385
Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.
A Study on Context Aware Middleware Design and Application
Jang, Dong-Wook ; Sohn, Surg-Won ; Han, Kwang-Rok ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 393~402
DOI : 10.3745/KIPSTD.2011.18D.5.393
This paper describes a design and application of middleware that is essential to the context-aware system. We define a transducer interface protocol in order to deal with a variety of context data. For the purpose of systematic process of data between middleware modules, a message oriented middleware is designed and implemented. Memory improves the performance of high-performance computing system compared to previous strategies. Context aware middleware adopts service oriented architecture so that functions in modules may be independent and scalability can be remarkable. Using messages across modules decreases the complexity of the application development. In order to justify the usefulness of the proposed context aware middleware, we carried out our experiments in bridge health monitoring system and verified the efficacy.
Design and Implementation of a MetaService for Improving Object Transfer among Applications on Android Platform
Choe, Hwa-Yeong ; Park, Sang-Won ;
The KIPS Transactions:PartD, volume 18D, issue 5, 2011, Pages 403~414
DOI : 10.3745/KIPSTD.2011.18D.5.403
Recently, smart phones based on Android platform have been widely used, and lots of applications have been developed. Data generated from an application are frequently transferred to other applications. Therefore, a method that can easily transfer or share meta-data among applications is required. Generally meta-data created by android applications are java objects. The android platform uses clipboard, intent and content provider in order to transfer data among the applications. However, those ways are designed to transfer data as a record. So these methods have to marshall the object to a record and unmarshall the record to an object. In this paper, we designed and implemented the MetaService which can transfer any type of object made by applications. When the MetaService is used, we can reduce complex implementations such as clipboards and content providers and we can reduce many bugs. Therefore, we can make the applications simple and increase productivity.