• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.945-960
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• 2009

The purpose of this study is to define determinants of VoIP user acceptance and to verify significant causality among latent variables - performance expectancy, effort expectancy, cost expectancy, social influence, facilitating conditions, behavioral intend, use behavior - based on UTAUT model. We presented the expanded hypotheses including the new factor, cost expectancy and analyzed the moderating effect of user age, gender and usage experience variables. For a accuracy of predicted results, we focused on survey analysis with 641 real user samples. Compared to previous studies, it is meaningful that this research verified the conceptual difference between behavioral intention and usage behavior. As a result, all proposed hypotheses accepted and moderating effects are supported significantly in age and use experience moderating variables.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.473-480
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• 2019

The smart home is a technology that can monitor and control by connecting everything to a communication network in various fields such as home appliances, energy consumers, and security devices. The Smart home is developing not only automatic control but also learning situation and user's taste and providing the result accordingly. This paper proposes a model that can provide a comfortable indoor environment control service for the user's characteristics by detecting the user's behavior as well as the automatic remote control service. The whole system consists of ESP 8266 with sensor and Wi-Fi, Firebase as a real-time database, and a smartphone application. This model is divided into functions such as learning mode when the home appliance is operated, learning control through learning results, and automatic ventilation using indoor and outdoor sensor values. The study used moving averages for temperature and humidity in the control of home appliances such as air conditioners, humidifiers and air purifiers. This system can provide higher quality service by analyzing and predicting user's characteristics through various machine learning and deep learning.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.187-195
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• 2012

Smart phone allows advertisers to estimate customers behavior by selecting user context awareness information and gives users instant feed back about their behavior. Electronic equipments such as smart phone enable advertisers to advertise interesting product for each customers at the point of purchase. In this paper, we deal with the trends of Smart phone and internet based TV in the spotlight as the upcoming advertising media and propose the effective way of advertising, Smart Advertising model, which can give users advertising contents of their interesting product by collecting user context information from a variety of devices including N-screen in smart space. This model will induce modern people who live in flood of advertisements to buy products by providing interesting advertising contents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.239-246
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• 2021

In the field of computer graphics and HCI, there are many studies on systems that create characters and interact naturally. Such studies have focused on the user's response to the user's behavior, and the study of the character's behavior to elicit positive emotions from the user remains a difficult problem. In this paper, we develop a prototype of an interaction system to elicit positive emotions from users according to the movement of virtual characters using artificial intelligence technology. The proposed system is divided into face recognition and motion generation of a virtual character. A depth camera is used for face recognition, and the recognized data is transferred to motion generation. We use imitation learning as a learning model. In motion generation, random actions are performed according to the first user's facial expression data, and actions that the user can elicit positive emotions are learned through continuous imitation learning.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.10-20
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• 2024

As the online commerce market continues to expand with an increase of diverse products and content, users find it challenging in navigating and in the selection process. Thereafter both platforms and shopping malls are actively working in conducting continuous research on recommendations system to select and present products that align with user preferences. Most existing recommendation studies have relied on user data which is relatively easy to obtain. However, these studies only use a single type of event and their reliance on time dependent data results in issues with reliability and complexity. To address these challenges, this paper proposes a recommendation system that analysis user preferences in consideration of the relationship between various types of event data. The proposed recommendation system analyzes the correlation of multiple events, extracts weights, learns the recommendation model, and provides recommendation services through it. Through extensive experiments the performance of our system was compared with the previously studied algorithms. The results confirmed an improvement in both complexity and performance.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.61-95
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• 2007

Small-and-medium sized enterprises(SMEs) represent quite a large proportion of the industry as a whole in terms of the number of enterprises or employees. However researches on information system so far have focused on large companies, probably because SMEs were not so active in introducing information systems as larger enterprises. SMEs are now increasingly bringing in information systems such as ERP(Enterprise Resource Planning Systems) and some of the companies already entered the stage of ongoing use. Accordingly, researches should deal with the use of information systems by SME s operating under different conditions from large companies. This study examined factors and mechanism inducing faithful appropriation of information systems, in particular integrative systems such as ERP, in view of individuals` active feedback-seeking behavior. There are three factors expected to affect end users` feedback-seeking behavior for faithful appropriation of information systems. They are management support, peer IT champ support, and IT staff support. The main focus of the study is on how these factors affect feedback-seeking behavior and whether the feedback-seeking behavior plays the role of mediator for realizing faithful appropriation of information systems by end users. To examine the research model and the hypotheses, this study employed an empirical method based on a field survey. The survey used measurements mostly employed and verified by previous researches, while some of the measurements had gone through minor modifications for the purpose of the study. The survey respondents are individual employees of SMEs that have been using ERP for one year or longer. To prevent common method bias, Task-Technology Fit items used as the control variable were made to be answered by different respondents. In total, 127 pairs of valid questionnaires were collected and used for the analysis. The PLS(Partial Least Squares) approach to structural equation modeling(PLS-Graph v.3.0) was used as our data analysis strategy because of its ability to model both formative and reflective latent constructs under small-and medium-size samples. The analysis shows Reliability, Construct Validity and Discriminant Validity are appropriate. The path analysis results are as follows; first, the more there is peer IT champ support, the more the end user is likely to show feedback-seeking behavior(path-coefficient=0.230, t=2.28, p<0.05). In other words, if colleagues proficient in information system use recognize the importance of their help, pass on what they have found to be an effective way of using the system or correct others' misuse, ordinary end users will be able to seek feedback on the faithfulness of their appropriation of information system without hesitation, because they know the convenience of getting help. Second, management support encourages ordinary end users to seek more feedback(path-coefficient=0.271, t=3.06, p<0.01) by affecting the end users' perceived value of feedback(path-coefficient=0.401, t=6.01, p<0.01). Management support is far more influential than other factors that when the management of an SME well understands the benefit of ERP, promotes its faithful appropriation and pays attention to employees' satisfaction with the system, employees will make deliberate efforts for faithful appropriation of the system. However, the third factor, IT staff support was found not to be conducive to feedback-seeking behavior from end users(path-coefficient=0.174, t=1.83). This is partly attributable to the fundamental reason that there is little support for end users from IT staff in SMEs. Even when IT staff provides support, end users may find it less important than that from coworkers more familiar with the end users' job. Meanwhile, the more end users seek feedback and attempt to find ways of faithful appropriation of information systems, the more likely the users will be able to deploy the system according to the purpose the system was originally meant for(path-coefficient=0.35, t=2.88, p<0.01). Finally, the mediation effect analysis confirmed the mediation effect of feedback-seeking behavior. By confirming the mediation effect of feedback-seeking behavior, this study draws attention to the importance of feedback-seeking behavior that has long been overlooked in research about information system use. This study also explores the factors that promote feedback-seeking behavior which in result could affect end user`s faithful appropriation of information systems. In addition, this study provides insight about which inducements or resources SMEs should offer to promote individual users' feedback-seeking behavior when formal and sufficient support from IT staff or an outside information system provider is hardly expected. As the study results show, under the business environment of SMEs, help from skilled colleagues and the management plays a critical role. Therefore, SMEs should seriously consider how to utilize skilled peer information system users, while the management should pay keen attention to end users and support them to make the most of information systems.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.1
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• pp.19-37
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• 2014

Server transaction logs containing complete click-through data from a digital library of primarily image-based documents were analyzed to better understand user search session behavior. One month of data was analyzed using descriptive statistics and network analysis methods. The findings reveal iterative search behaviors centered on result views and evaluation and topical areas of focus for the search sessions. The study is novel in its combined analytical techniques and use of click-through data for image collections.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.144-152
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• 2009

To provide intelligent service in mobile environment, it needs to estimate user's intention or requirement, through analyzing context information of end-users such as preference or behavior patterns. In this paper, we infer context information from uncertain log stored in mobile device. And we propose the inference method of end-user's behavior to match context information with service, and the proposed method is based on context-tree. We adopt bayesian probabilistic method to infer uncertain context information effectively, and the context-tree is constructed to utilize non-numerical context which is hard to handled with mathematical method. And we verify utility of proposed method by appling the method to intelligent phone book service.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.247-253
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• 2020

It has emerged Food-content among various forms of 1-person media through social media. Food-content influencer also market products through 1-person media, generating revenue through increased views and subscribers of 1-person media. It also sells products through sponsorship. In general, there is a profit structure through 1-person media viewing, but research on how restaurant companies generate profits directly through food-content is insufficient. In addition, research on converting subscribers to consumers through food-contents is minimal. In this paper, we propose an experiential application system based on the behavior of food-content creators. The proposed system collects and categorizes food-content information, and maps between highly related words to organize into keyword categories. The ontology tag-based concept network applied to the proposed system connects representative information by pre-extracting/mapping information related to information requests among a wide range of data. This method maps relevant food-content information to provide the user with data collected/storage in the form of an application. The user uses the application while watching the food eaten by the influencer and creator. And, it is meaningful that the user could be provided is provided with information about the food they want to eat.