• Journal of Internet Computing and Services
• /
• v.25 no.4
• /
• pp.109-119
• /
• 2024

This study aims to contribute to the initial research on on-device AI in an environment where generative AI-based services on mobile and other on-device platforms are increasing. To derive success strategies for generative AI-based chatbot services in a mobile environment, over 200,000 actual user experience review data collected from the Google Play Store were analyzed using the LDA topic modeling technique. Interpreting the derived topics based on the Information System Success Model (ISSM), the topics such as tutoring, limitation of response, and hallucination and outdated informaiton were linked to information quality; multimodal service, quality of response, and issues of device interoperability were linked to system quality; inter-device compatibility, utility of the service, quality of premium services, and challenges in account were linked to service quality; and finally, creative collaboration was linked to net benefits. Humanization of generative AI emerged as a new experience factor not explained by the existing model. By explaining specific positive and negative experience dimensions from the user's perspective based on theory, this study suggests directions for future related research and provides strategic insights for companies to improve and supplement their services for successful business operations.

• Archives of design research
• /
• v.17 no.2
• /
• pp.199-208
• /
• 2004

In cyberspace based on internet, users constitute communities and interact one another. Avatar means not only the other self but also the 'another being' that describes oneself in the cyberspace. If user's avatar shows expressive faces and behaves according to his thinking and emotion, he will have a feel of reality much more in the cyberspace. If avatar's countenances can be animated by just typing characters in avatar-based chat communication, the user is able to express his emotions more effectively. In this study, emotion-expressing vocabulary is analyzed and classified. Emotion-expressing vocabulary is essential to develop self-reactive avatar system in which avatar's countenances are automatically converted according to the words typed by users at chat. The results are as follows; First, emotion-expressing vocabulary selected out of Korean adjectives and intransitive verbs is made up of 209 words and is classified into 25 groups. Second, there are only 2 groups out of the 25 groups for positive expressions and others are for negative expressions. Therefore, negative expressions are more abundant than positive expressions in Korean vocabulary. Third, avatar's countenances are modelled according to the 25 groups by using the Quantification Method 3. The result shows that the emotion-expressing vocabulary has dose relations with avatar's countenances and is useful to communicate users' emotions. However, this study has some limits, in that Korean linguistical structure - the whole meaning of context - cannot be interpreted quantitatively.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.7
• /
• pp.257-268
• /
• 2017

The purpose of this study was to examine the anxiety, levels of diabetes-related distress, and post-traumatic growth of parents who have children with type 1 diabetes and determine the correlation between the differences and variables based on the general characteristics and disease-related characteristics. This is a descriptive survey research and data collection was conducted from January 4th-29th of 2016 with an online survey in an internet community for type 1 diabetes. Seventy seven individuals were included in the final analysis. Statistical analysis was carried out with a t-test, Mann-Whitney U test, Kruskal-Wallis test, and Pearson correlation coefficient. The study results showed that posttraumatic growth was significantly high (p<.05) under parents with a religion, and that parental anxiety and stress were high with children under 6 years of age (p<.05), with cases of hypoglycemia (p<.05), and with high levels of glycated hemoglobin (p<.05). Anxiety and stress had a positive correlation (r=.684, p<.001), and anxiety and stress exhibited a negative correlation with posttraumatic growth (r=-.401, p<.001; r=-.327, p<.05). This suggests that posttraumatic growth can reduce the negative emotions sufficiently, and that a mediating mechanism is needed that promotes posttraumatic growth while decreasing the level of anxiety and stress.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.4
• /
• pp.811-817
• /
• 2009

The rapid growth of network based IT systems has resulted in continuous research of security issues. Probe intrusion detection is an area of increasing concerns in the internet community. Recently, a number of probe intrusion detection schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of probe intrusion. They can not detect new patterns of probe intrusion. Therefore, it is necessary to develop a new Probe Intrusion Detection technology that can find new patterns of probe intrusion. In this paper, we proposed a new network based probe intrusion detector(NePID) using anomaly traffic analysis and fuzzy cognitive maps that can detect intrusion by the denial of services attack detection method utilizing the packet analyses. The probe intrusion detection using fuzzy cognitive maps capture and analyze the packet information to detect syn flooding attack. Using the result of the analysis of decision module, which adopts the fuzzy cognitive maps, the decision module measures the degree of risk of denial of service attack and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.094% and the max-average false negative rate of 2.936%. The true positive error rate of the NePID is similar to that of Bernhard's true positive error rate.

• Journal of Distribution Research
• /
• v.17 no.3
• /
• pp.93-113
• /
• 2012

Early conflict research in channel and organization area have focused on the definition of conflict construct, its cause, consequence and identified conflict resolution management. Recent studies about conflict, however, have explored new assumption of complexity, a multidimensional conflict construct, contextual conflict management strategies, positive and negative conflict/consequence, and the conflict resolution strategy. Although many literatures exists on channel conflict resolution, little research has been done about relationship learning and performance from conflict resolution perspective. This study explores how channel members can achieve a relationship learning, as a conflict resolution mechanism, which enhance co-created value in marketing channel relationship. Therefore we propose that conflict resolution strategies(collaborating behavior and avoiding behavior) influence channel performance(effectiveness and efficiency) through relationship learning processes(learning via information exchange, joint interpretation and coordination, relationship-specific knowledge memory), in view of buyer-seller relationship. The research model is shown at

• Journal of KIISE:Software and Applications
• /
• v.34 no.1
• /
• pp.40-51
• /
• 2007

To improve academic achievement, the most students not only participate in regular classes but also take various extra programs such as private lessons, private institutes, and educational TV programs. In this paper, we propose a data mining approach to identify which studying methods or usual life patterns during a school vacation affect changes in the academic achievement. First, we derive various studying methods and life patterns that are thought to be affecting changes in the academic achievement during a school vacation. Second, we propose the method of transforming and analyzing data to apply them to decision trees and association rules, which are representative data mining techniques. Third, we construct decision trees and find association rules from the real survey data of middle school students. We have discovered four representative results from the decision trees. First, for students in the higher rank, there is a tendency that private institutes give a positive effect on the academic achievement. Second, for the most students, the Internet teaming sites nay give a negative effect on the achievement. Third, private lessons that have thought to be making a large impact to the achievement, however, do not make a positive effect on the achievement. Fourth, taking several studying methods in parallel nay give a negative effect on the achievement. In association rules, however, we cannot find any meaningful relationships between academic achievement and usual life patterns during a school vacation. We believe that our approach will be very helpful for teachers and parents to give a good direction both in preparing a studying plan and in selecting studying methods during a school vacation.

• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.105-118
• /
• 2021

This study pays attention to the fact that the fake news is attracting attention because it causes various social problems. To find out these fake news' influence, the study conducted the experiment to examine that the fake news related to the electronic voting system affects on the news users' attitude of using the system, intention to participate in the election through the system and reliability of news services. The results have shown that the fake news framed with negative contents reduced users' attitude of using the system and intention of participation in the election. Especially, as a result of examining the difference in the fake news' influence according to each news services, in the case that users recognized that the news was fake after exposing to the general internet news, the attitude of using the system and the intention of participation in the election have reduced and recovered again. However, users who exposed to Naver, Facebook believed the negative content of the fake news more strongly. Through these results, this study empirically confirmed that the fake news has a tendency to exert influence on users' cognitive dimension and to reinforce awareness in a direction consistent with the initial exposure information.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.165-187
• /
• 2023

The continuous increase in life expectancy and high interest in health has brought about significant changes in the use of health information by the public according to the development of information technology represented by the Internet and smartphones. As the medical market expands to the mobile health environment, many health-related apps have been created and distributed, but the acceptance rate is slow as it has become challenging to provide services due to various regulations. In this study, perceived value, perceived risk factors (psychological risk, risk of time-loss, legal risk), and perceived benefits (usefulness, interaction, autonomy) were derived and verified as factors that affect the acceptance resistance of personal health record apps based on the privacy calculation model. In addition, by analyzing the moderating effect of trust in the manufacturer, how the perceived risk and perceived benefit affect the perceived value was verified. A survey was conducted on Korean college students who recognized the personal health record apps but did not use them, and 127 samples were analyzed using structural equations. As a result of hypothesis verification, perceived value has a negative effect on acceptance resistance, perceived risk (risk of time-loss) has a negative effect on perceived value, and perceived benefits (usefulness, interaction, autonomy) were found to have a positive effect on perceived value. Trust in manufacturers has weakened the impact of perceived risks (legal risk) on perceived values. This study is expected to play an important role in maintaining a competitive advantage in the personal health record app market environment by identifying and proposing detailed criteria for reducing the acceptance resistance of personal health record apps.

• 한국벤처창업학회:학술대회논문집
• /
• 2007.04a
• /
• pp.405-433
• /
• 2007

This study is conducted to examine how purchase behaviors of consumers have affected by the promotion of coupons in internet shopping mall. This study was conducted with the purpose of identifying the differences in purchase behavior based on consumer' s perception and experience of internet shopping mall coupons, and based on consumers' perception of cost and value of coupons, using a theoretic framework presented in previously conducted studies. The results of this study can be summarized as follows. First, based on the perception of coupons, there were significant differences in intent to use and intent to re-use at the time when coupons are offered, and at the time when coupons are offered, no significant differences were found between the level of interest and the importance of coupon at the time of visiting the shopping mall; however, significant differences were found in the overall purchase behavior based on perception of coupons. Second, when overall differences m purchase behavior based on experience in coupon use was observed, having experience in using coupons showed a higher average than did having no experience in using coupons, showing a significant difference. It was found that compared to those without experience in using coupons, those with experience with coupons had higher intent to use at the time when coupon is offered, intent to re-use at the time when coupon is offered, and higher level of purchase behavior in the importance of coupons at the time of visiting the shopping mall. Third, when relationship between purchase behaviors, cost of coupon, and perception of convenience was observed, a clear static relationship was found. This suggests that as the cost and perception of convenience of coupon increases, purchase behavior also increases. Such result suggests that there is a difference in purchase behavior based on experience in coupon use. When relationship of purchase behavior by variables of cost of coupon and perception of convenience is observed, it has a positive relationship with the perception that the use of coupon includes saving money, financial help, enjoyment of use, habitual use, has a short effective date, and has a negative relationship with the perception that it saves little money and is a waste of time. Therefore, it can be seen that purchase behavior has the highest relationship with enjoyment of coupon use and habitual coupon use. Such results suggest that purchase behavior will be significantly influenced based on cost of coupon and perception of convenience.

• Journal of Intelligence and Information Systems
• /
• v.21 no.4
• /
• pp.37-51
• /
• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.