• The Journal of Information Systems
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• v.28 no.4
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• pp.271-291
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• 2019

Purpose The purpose of this study is to propose a methodology to derive positive keywords and negative keywords through deep learning to classify reviews into positive reviews and negative ones, and then refine the results of topic modeling using these keywords. Design/methodology/approach In this study, we extracted topic keywords by performing LDA-based topic modeling. At the same time, we performed attention-based deep learning to identify positive and negative keywords. Finally, we refined the topic keywords using these keywords as filters. Findings We collected and analyzed about 6,000 English reviews of Gyeongbokgung, a representative tourist attraction in Korea, from Tripadvisor, a representative travel site. Experimental results show that the proposed methodology properly identifies positive and negative keywords describing major topics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.87-97
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• 2019

Reaction of people is importantly considered about specific case as a social network service grows. In the previous research on analysis of social network service, they predicted tendency of interesting topic by giving scores to sentences written by user. Based on previous study we proceeded research of sentiment analysis for social network service's sentences, which predict the result as positive or negative for movie reviews. In this study, we used movie review to get high accuracy. We classify the movie review into positive or negative based on the score for learning. Also, we performed embedding and morpheme analysis on movie review. We could predict learning result as positive or negative with a number 0 and 1 by applying the model based on learning result to social network service. Experimental result show accuracy of about 80% in predicting sentence as positive or negative.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.223-226
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• 2009

Recently, Mining negative association rules has received some attention and proved to be useful. Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other. Several algorithms have been proposed. However, there are some questions with those algorithms, for example, misleading rules will occur when the positive and negative rules are mined simultaneously. The chi-squared test that based on the mature theory and Correlation Coefficient can avoid the problem. In this paper, We proposed the algorithm PNCCR based on chi-squared test and correlation is proposed. The experiment results show that the misleading rules are pruned. It suggests that the algorithm is correct and efficient.

• Annual Conference of KIPS
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• 2023.11a
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• pp.418-421
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• 2023

본 논문은 Word2Vec를 이용하여 한국어 증상 기반 질병 예측 모델을 제시한다. 아산병원 질환 백과의 크롤링 데이터를 세 가지 형식으로 나누어, 모델에 알맞은 데이터 형식을 찾고 모델에 적용한다. 가장 모델에 맞는 데이터 형식은 증상별 질병과 질병별 증상을 합친 경우이다. 데이터의 양을 늘려 임베딩 스페이스를 넓혔고, 가장 중요한 증상과 질병의 유사도도 정확하게 출력되었다. 이는 유사도가 높은 질병과 증상들이 제대로 학습이 되었다는 것을 알 수 있다. 이렇게 만들어진 예측 모델에 positive 증상을 입력하면 유사도가 향상되고, negative에 입력하면 하락하는 결과를 확인했다. 따라서 환자의 증상을 positive에 넣으면, 그 증상을 가진 질병이 가까워지는 반면, 환자의 증상이 아닌 증상을 negative에 넣으면, 환자에게 맞지 않는 질병이 멀어진다. 그러므로 환자의 상태에 맞는 질병을 유추해, 의사나 환자가 증상에 대한 질병을 알고 싶을 때 또는 검색에 유용하게 사용할 수 있다. 더불어, 질병의 진료과 데이터를 추가하여, 환자에게 맞는 진료과를 찾는 데도 도움을 줄 수 있다.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.1-20
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• 2020

Malicious rumors often emerge online. However, few studies have examined why people spread online rumors. Recognizing that spreading online rumors is not only rational, but also emotional, this paper provides insights into the behavior of online rumor spreading using the cognitive emotion theory. The results show that perceived credibility of online rumors enhances both positive and negative emotions. However, positive emotions affect neither attitude nor behavior, whereas negative emotions affect both aspects of the spreading of online rumors. The results also indicate that prior positive attitude toward object influences negative emotions. Issues involvement moderates the relationship between attitude and behavior.

• Journal of Information Technology Services
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• v.23 no.2
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• pp.83-97
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• 2024

This study was conducted to examine the effect of institutional mechanisms on customers' trust and continuous purchase intention in open market platforms, The research frame was expanded by setting institutional situations into positive and negative areas in order to examine the relationship between institutional mechanisms and trust in multiple dimensions. The results of this study confirmed that the feedback system, dispute resolution, and intermediary trust factors affect trust in positive areas, and dispute resolution, information security, and intermediary trust affect buyer trust in negative areas. For the relationship between trust and repurchase intention, it was confirmed that if the institutional situation is positive, trust leads to repurchase intention, and in negative areas, trust does not lead to repurchase intention. The results of this study show that institutional mechanisms are a key factor in building trust in online platforms according to institutional circumstances and play a role in offsetting trust in platforms in negative areas.

• Culinary science and hospitality research
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• v.22 no.8
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• pp.109-121
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• 2016

This study analyzed the effect of five sub-variables' attribute of HMR: features of information, diversity, promptness, price and convenience, on the consumer purchasing intention. In addition, the regulation effect of positive reviews and negative reviews of consumers' online reviews between HMR selection attribute and purchasing intention was also tested. Results are following. First, convenience feature (B=.577, p<.001) and diversity feature (B=.093, p<.01) among the effect of HMR selection attribute had a positive (+) effect on purchasing intention. On the other hand, promptness feature (B=.235, p<.001) and price feature (B=.161, p<.001), and information feature (B=.288, p<.001) were not significant effect on purchasing intention. Second, result of regulation effect of the positive reviews of consumer's online review between the selection attribute of the HMR product and consumers' purchasing intention, in the first-stage model in which the selection attribute of the HMR product is input as an independent variable, there was a significant positive (+) effect on all the features of convenience, diversity, promptness, price, and information. In addition, there was significant positive (+) main effect (B=.472, p<.001) in the second step model in which the consumers' positive reviews, that is a regulation variable. Furthermore, the feature of price (B=.068, p<.05) had a significant positive (+) effect in the third stage in which the selection attribute of the HMR product that is an independent variable and the interaction of the positive review. However, the feature of information (B=-.063, p<.05) showed negative (-) effect, and there was no effect on the features of convenience, diversity, and promptness. Third, as a result of testing the regulation effect of the negative reviews of consumers' online reviews between HMR product selection attribute and consumers' purchasing intention, in the first-stage model in which the selection attribute of the HMR product was a positive (+) effect on all the features of convenience, diversity, promptness, price, and information. In the second-stage model in which consumers' negative reviews (B=-.113, p<.001) had negative (-) effect. In the third-stage in which the selection attribute of the HMR product and the interactions of the negative reviews was a positive (+) effect with the feature of price (B=.113, p<.01). Last, there was no effect at all on the features of convenience, promptness, and information.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.245-253
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• 2007

In this paper, the existence of bounded positive solution of the second-order nonlinear neutral differential equations are studied. Some new sufficient conditions are given. Furthermore, examples given show that the results here are almost sharp.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.767-772
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• 2007

A kernel machine is proposed as an estimating procedure for the linear and nonlinear Poisson regression, which is based on the penalized negative log-likelihood. The proposed kernel machine provides the estimate of the mean function of the response variable, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation(GCV) function of MSE-type is introduced to determine hyperparameters which affect the performance of the machine. Experimental results are then presented which indicate the performance of the proposed machine.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.331-337
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• 2015

A novel fully-printed microstrip antenna with negative first resonance and dual polarization is proposed. The radiator is printed on the 1-layer substrate instead of multilayers. The -1st resonance results from a composite right- and left-handed(CRLH) structure that has a circumferentially interlocked gap capacitively coupling a patch with a shorted-ring. This compact antenna is provided with a dual-polarization capability by creating two orthogonal linear polarizations in one body with coaxial feeds. The design is carried out by doing full-wave EM field simulation which is compared with the measurement of the fabricated antenna prototype. The measured results give the gain of 5 dBi and the efficiency of 78% at the -1st resonance mode as the center frequency of a downlink channel of the bandwidth over 20 MHz with 29 dB polarization isolation for mobile communication.