• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.77-81
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• 2016

Logistic regression (LR) has been widely used for predicting the relationships among variables in various fields. We propose a new logistic regression model with a fine-grained weighting method, called value weighted logistic regression, by assigning different weights to each feature value. A gradient approach is utilized to obtain the optimal weights of feature values. We conduct experiments on several data sets and the experimental results show that the proposed method shows meaningful improvement in prediction accuracy.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.7
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• pp.1020-1027
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• 2012

The purpose of this study was to investigate the priority of menu management by importance-performance analysis (IPA) of school foodservice menu attributes. Questionnaires were distributed to 448 school dietitians with an official letter, and a total of 292 responses were used for analysis. From the 21 menu attributes, the factors of 'nutrition', 'educational effect', 'capability consideration', 'ease of quality management', 'efficiency', and 'preference of students' were induced from exploratory factor analysis. The levels of importance (p<0.01) and performance (p<0.05) of the 'nutrition' factor were significantly higher with nutrition teachers than school dietitians, while the importance of the 'preference of students' factor showed significantly higher score with school dietitians (p<0.05). As a result of gap analysis for IPA, only the 'efficiency' factor was located in the area where performance was higher than importance, whereas no menu attribute factors were included in the 'concentrate here' area by the usual IPA. Further analysis showed that there should be more effort to improve the performance of an 'educational effect' factor for a school foodservice menu.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.115-126
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• 2022

The purpose of this study is to try to IPA(Importance-Performance Analysis) by applying text mining approaches to user review data for korea mobile banking applications, and to derive priorities for improvement. User review data on mobile banking applications of korea commercial banks (Kookmin Bank, Shinhan Bank, Woori Bank, Hana Bank), local banks (Gyeongnam Bank, Busan Bank), and Internet banks (Kakao Bank, K-Bank, Toss) that gained from Google playstore were used. And LDA topic modeling, frequency analysis, and sentiment analysis were used to derive key attributes and measure the importance and satisfaction of each attribute. Result, although 'Authorizing service', 'Improvement of Function', 'Login', 'Speed/Connectivity', 'System/Update' and 'Banking Service' are relatively important attributes when users use mobile banking applications, their satisfaction is not at the average level, indicating that improvement is urgent.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.8
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• pp.802-813
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• 2012

This study establishes how the clothes consumption value, need for uniqueness, and use information sources could influence the importance of apparel product attributes and the importance of store attributes. Data were collected through a survey of adults in their 20's and 30's with 48 questionnaires for statistical analysis. The collected data were processed with the programs AMOS 16.0 and SPSS 18.0 for windows and reliability analysis, correlation analysis, factor analysis, and structural equation analysis were conducted to analyze the data. The results in this research are follows. First, the clothes consumption value influences the importance of apparel product attributes both directly and indirectly and the importance of store attributes indirectly through use information sources. Second, the need for uniqueness influences the importance of apparel product attributes indirectly and importance of store attributes both directly and indirectly through clothes consumption value and use information sources. The implications of these findings and suggestions for future study are also discussed.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.1
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• pp.123-131
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• 2017

The aim of this paper was to provide basic data on revitalizing traditional markets in 389 undergraduate students who had purchased foods sold at a traditional market in order to understand the current state of usage of traditional market foods and to analyze degree of importance and satisfaction. From September 2015 to November 2015, questionnaires were filled out by respondents. Of the 389 questionnaires that were returned, 343 were used while 46 were discarded as incomplete. In the traditional market, high popularity was detected in foods such as 'Hotteok', 'stir-fried rice cake', 'Korean sausage', and so on in that order, which were mainly simple foods. There was a tendency that 'taste', 'hygiene', 'price', and 'quality' were considered as important, all of which scored more than 4 points for all residence types. In the difference analysis of the degree of satisfaction and importance in traditional market foods according to residence types, degree of importance was much higher than that of satisfaction for all selective attributes. In the results of ISA analysis for attributes of traditional market foods, those selling food in the second quadrant need to make more effort to improve 'hygiene' and 'quality' of food.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.1036-1041
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• 2008

본 연구는 UCC를 이용하는 동기와 UCC전문 사이트의 웹 사이트 속성 및 UCC컨텐츠 속성과 UCC이용 행태간의 관계를 살펴보았다. 그 결과, 정보추구, 오락, 사회, 경제적 UCC이용동기에 따라 UCC사이트에서 중요시하는 속성, 컨텐츠에서 중요시하는 속성이 다르게 나타났다. 이 결과를 통해 좀 더 사용자 친화적인 UCC사이트 개발로 경쟁력 확보 및 차별화 방안을 모색해 보고자 한다.

• Korean Journal of Environment and Ecology
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• v.17 no.4
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• pp.366-374
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• 2004

The purpose of this study is to develop effective destination management strategies for three typical tourist destinations in Kangwon province based on the importance-performance analysis. The results show that overall performance levels of 21 management attributes in three destinations is relatively low, compared to the importance levels of the attributes. 6 attributes place in Concentrate Here, 4 attributes in Possible Overkill, 6 attributes in Keep Up Good Work, and 5 attributes in Low Priority. There is no significant difference in the importance level among three destinations, while performance levels are the lowest at Naksan & Kyungpo beaches, and highest at Ganhyun area. Findings of the survey expect to be used as fundamentals in management policy making process for each destinations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2379-2386
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• 2016

This study conducted an analysis using IPA metrics targeting college students to get strategic implications for marketing in the recently fast-growing mobile shopping market. The IPA analysis result about the selection of mobile shopping malls is as follows. First, out of the 21 features, 'reliability of the offered products(6.09)' had the highest level of importance and 'convenience of payment(5.29)' had the highest level of performance. Second, in the area of 'Doing great, Keep it up' 11 features were included such as 'convenience of payment' and 'reliability of the offered products'. Third, the feature that needed to be corrected in the area of 'Focus here' was 'shortening the waiting time for exchange, refund or warranty service'. Fourth, low priority areas in terms of importance and performance, there were 3 features including 'push/notification helps purchases'. Fifth, to the area of 'overdone' 4 features belonged such as 'variety in the type of products'.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.652-654
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• 2021

Attacks such as DDoS are detected by the intrusion detection system and can be prevented early. DDoS attack traffic was analyzed using the decision tree. Deterministic features with high importance were found, and the accuracy was verified by proceeding the decision tree for only those properties. And the contents of false positive and false negative traffic were analyzed. As a result, the accuracy of one attribute was 98% and the two attributes were 99.8%, respectively.

• Journal of KIISE
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• v.43 no.11
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• pp.1270-1274
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• 2016

Logistic regression is widely used for predicting and estimating the relationship among variables. We propose a new logistic regression model, the value weighted logistic regression, which comprises of a fine-grained weighting method, and assigns adapted weights to each feature value. This gradient approach obtains the optimal weights of feature values. Experiments were conducted on several data sets from the UCI machine learning repository, and the results revealed that the proposed method achieves meaningful improvement in the prediction accuracy.