• Journal of KIISE:Databases
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• v.33 no.7
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• pp.727-740
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• 2006

Schema matching is important as a prerequisite to the transformation of XML documents. This paper presents a schema matching method for the transformation of XML documents. The proposed method consists of two steps: preliminary matching relationships between leaf nodes in the two XML schemas are computed based on proposed ontology and leaf node similarity, and final matchings are extracted based on a proposed path similarity. Particularly, for a sophisticated schema matching, the proposed ontology is incrementally updated by users' feedback. furthermore, since the ontology can describe various relationships between concepts, the proposed method can compute complex matchings as well as simple matchings. Experimental results with schemas used in various domains show that the proposed method is superior to previous works, resulting in a precision of 97% and a recall of 83 % on the average. Furthermore, the dynamic ontology increased by 9 percent overall.

• The Journal of the Korea Contents Association
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• v.14 no.2
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• pp.482-493
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• 2014

Many kinds of carbon emission monitoring systems or integrated systems have been developed so far. However, despite of the development of related techniques, they tend to be lack of statistic processing functions for feedback and policy-making data for users. In this study, a new CEMS (Carbon Emission Monitoring System) has been suggested and implemented in Sejong City, Korea. This system adapted automatic remote reading system from the site management agency as data hub to collect the electricity, gas and water usage of each household. The CEMS is consisted of 6 parts; carbon emission measurement, carbon emission standard setup and management, statistic analysis and the incentives. CEMS is distinguished with other systems for its UIs for users and the administrators. Also, data sharing with urban information system(UIS) of local government to produce information for users and policy-makers. This system makes it possible to investigate the change of energy consumption patterns, especially depending on the family structure and the housing characteristics. Furthermore, analyzing their correlation with carbon emission, it is expected to provide basic data used to establish urban environmental policies.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.66-73
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• 2007

Internet is a part of our common life and tremendous information is cumulated. In these trends, the personalization becomes a very important technology which could find exact information to present users. Previous personalized services use content based filtering which is able to recommend by analyzing the content and collaborative filtering which is able to recommend contents according to preference of users group. But, collaborative filtering needs the evaluation of some amount of data. Also, It cannot reflect all data of users because it recommends items based on data of some users who have similar inclination. Therefore, we need a new recommendation method which can recommend prefer items without preference data of users. In this paper, we proposed the apparel coordination system using personalized preference on the semantic web. This paper provides the results which this system can reduce the searching time and advance the customer satisfaction measurement according to user's feedback to system.

• Proceedings of the CALSEC Conference
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• 2002.01a
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• pp.135-154
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• 2002

As the use of Information Technology is increasing, various kinds of IT service vendor proliferate. And most executives are trying to expand their field to online world. As the emphasis on Information Technology is inevitable, executives want to evaluate the service level they receive from IT service vendor. But. there's not yet the proper evaluation system for IT service. The evaluation systems like CMM, SPICE are process-focused. They don't give a look on the final product delivered to customer. On the other hand, the one that evaluate the customer satisfaction like ACSI, NCSI are too over-focused that they can't express the specific characteristics on the subjects that are deemed to evaluate. The focus is blurred. To overcome these limitations of existing framework, and to increase the value of evaluation, this study presents the evaluation system of IT service (afterwards, named as 'The new evaluation system') that derives process factors from IT service CMM, and evaluate customer satisfaction of IT service. Finally, the model was applied to the actual case to examine the practicality of the framework.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1565-1574
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• 2010

While we are driving a car, we are able to listen to musics by two ways: by selecting (manipulating) what we want and by just playing as they are given (in CD). These methods make a driver tired while he is driving or it means that a music which is provided is not concerned with a driver's preference. To improve these problems, there have been many studies about the automatic music providing systems based on driver's emotion. However, these studies have some difficult problems: the first one is that it is not easy to determine driver's emotion, and the other one is that it is hard to recommend and play the suitable music corresponding to the determined user's emotion. In this paper, to overcome the second problem mentioned above, a new mapping method between driver's emotion and music genre for automatic music providing system on vehicle is presented and two experiments are examined for the validation of the proposed method. The experimental results and discussions are explored to show the effectiveness and validity of the proposed method.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.684-695
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• 2001

Recent recommender system uses a method of combining collaborative filtering system and content based filtering system in order to solve sparsity and first rater problem in collaborative filtering system. Collaborative filtering systems use a database about user preferences to predict additional topics. Content based filtering systems provide recommendations by matching user interests with topic attributes. In this paper, we describe a method for discovery of user preference through combining two techniques for recommendation that allows the application of machine learning algorithm. The proposed collaborative filtering method clusters user using genetic algorithm based on items categorized by Naive Bayes classifier and the content based filtering method builds user profile through extracting user interest using relevance feedback. We evaluate our method on a large database of user ratings for web document and it significantly outperforms previously proposed methods.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.103-112
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• 2018

In this paper, we propose a method of recognizing emotions using PPG sensor which measures blood flow according to emotion. From the existing PPG signal, we use a method of determining positive emotions and negative emotions in the frequency domain through PSD (Power Spectrum Density). Based on James R. Russell's two-dimensional prototype model, we classify emotions as joy, sadness, irritability, and calmness and examine their association with the magnitude of energy in the frequency domain. It is significant that this study used the same PPG sensor used in wearable devices to measure the top four kinds of emotions in the frequency domain through image experiments. Through the questionnaire, the accuracy, the immersion level according to the individual, the emotional change, and the biofeedback for the image were collected. The proposed method is expected to be various development such as commercial application service using PPG and mobile application prediction service by merging with context information of existing smart phone.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.97-100
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• 2009

The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 and 2000 using a dynamic technique, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series for tracking changes on the ground surface. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.41-47
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• 2007

The selection of the reasonable project delivery system (PDS) is crucial for a successful performance of a project, which means to achieve project objectives. Furthermore, the project performance has been tightly related to the selection of PDS appropriate to pertinent project characteristics. In this context, the ministry of finance and economy of Korea launched two new project delivery systems called "Best Value Contract (Design-Bid-Build)" and "Bridging Contract (Design-Build)" in October of 2007 by revising enforcement ordinances of "Act on Contracts to Which the State is a Party". For efficient operation of the new project delivery systems, this paper suggested a PDS selection model which supports decision making of the reasonable PDS for a pertinent project by assessing characteristics of the public construction projects, both quantitatively and qualitatively. In addition, a PDS performance evaluation model was proposed in order to get feedback on the result of the PDS selection and the operation for the succeeding project. The standard models suggested in this paper might be used as a tool to support the decision making of the public organizations.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.113-124
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• 2019

This is a convergence study to investigate the relationship between cereal intake level and food and nutrient intake in 218 Chinese middle aged women aged 40 to 65 years. Data were analyzed by ${\chi}^2$ test, ANOVA, correlation analysis and Jonckheere-Terpstra trend test using SPSS 22.0 program. The results of the study were as follows. The higher the level of cereal intake in the subjects, the lower were the rate of breakfast fasting (p for trend=0.000), overeating (p for trend=0.019), and eating out (p for trend=0.003). The intake of root and tuber crops(p for trend=0.008), meat(p for trend=0.043), pulses(p for trend=0.020), and light colored vegetables(p for trend=0.015) per 1,000 kcal of energy increased when the level of cereal intake was 6 to 9 units. Therefore, it is necessary to discuss and study for continuous education and improvement through the feedback so that the middle-aged women can take the cereal appropriately.