• The Journal of the Korea Contents Association
• /
• v.15 no.8
• /
• pp.481-494
• /
• 2015

Recently mobile application providers and telecommunication companies went through a difficult time in a highly competitive mobile and its application market where we've seen a huge trend for diverse mobile applications occurring on smart phone. If there were a time when those of companies need to analyze factors affecting users' intention to download or recommend others applications more than ever, it is now. Based on UTAUT model, this research is to provide them with strategic implications by analyzing those factors according to application types with utilization and hedonic values. As a result, firstly trust and personalization have positive impact on Performance Expectancy and users' intention to use have been significantly affected by Performance Expectancy and Effort Expectancy. Secondly the result of path analysis has a different outcome according to application types with utilization and hedonic values. Therefore it is expected that the research gives practical and strategic implication for application developer, mobile companies and others helping application development, new service launch and marketing implementation.

• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.223-233
• /
• 2019

The purpose of this study is to identify factors that influence HPV(human papilloma virus) vaccination intention and behavior for mothers with a teenage daughter as the subject of HPV vaccine free inoculation from 2016 based on the theory of planned behavior. For attitude, subjective norm, perceived behavior control, intention, we used a tool modified and supplemented by Hye-Min Park, Hyu-Ei Oh. from June to September 2017, data of 249 people were collected and analyzed by SPSS Statistics 21.0 program. The results of this study showed that the factors affecting the HPV vaccination intention of the subject were attitude, subjective norm, perceived behavior control in order. In addition, the factors influencing HPV vaccination behavior were found to be level of education, subject's vaccination status, recommendation of health care provider, vaccination status of surrounding people, intention etc. Therefore, in order to increase the vaccination rate, we need to find a way to consider the factors influencing vaccination behavior and maximize the vaccination rate.

• The Journal of the Korea Contents Association
• /
• v.22 no.10
• /
• pp.765-777
• /
• 2022

The purpose of this study is to present a digital transformation-based learning model that can be used in universities based on learning digital transformation in order f to be competitive in a rapidly changing environment. Literature review, case study, and focus group interview were conducted and the implications for the learning model from these are as follows. Universities that stand out in related fields are actively using learning analysis to implement dashboards, develop predictive models, and support adaptive learning based on big data, They also have actively introduced advanced edutech to classes. In addition, problems and difficulties faced by other universities and K University when implementing digital transformation were also confirmed. Based on these findings, a digital transformation-based learning model of K University was developed. This model consists of four dimensions: diagnosis, recommendation, learning, and success. It allows students to proceed with learning by diagnosing and recommending various learning processes necessary for individual success, and systematically managing learning outcomes. Finally, academic and practical implications about the research results were discussed.

• The KIPS Transactions:PartB
• /
• v.9B no.4
• /
• pp.389-390
• /
• 2002

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

• Journal of Internet Computing and Services
• /
• v.17 no.1
• /
• pp.15-21
• /
• 2016

Under the flag of creative economy, Korea government is now releasing public data in order to develop or provide a range of services. In this paper, we develop a customized trip navigation system to recommend a trip itinerary based on integration of open government data and personal tourist data. The system uses case-based reasoning (CBR) to provide a personalized trip navigation service. The main difference between existing trip information systems and ours is that our system can offers a user-oriented information service. In addition, our system supports Turn-key style contents provision to maximize convenience. Our system can be a good example of the way in which open government data can be used to design a new service.

• Journal of KIISE:Software and Applications
• /
• v.32 no.7
• /
• pp.581-591
• /
• 2005

Collaborative filtering systems have problems involving sparsity and the provision of recommendations by making correlations between only two users' preferences. These systems recommend items based only on the preferences without taking in to account the contents of the items. As a result, the accuracy of recommendations depends on the data from user-rated items. When users rate items, it can be expected that not all users ran do so earnestly. This brings down the accuracy of recommendations. This paper proposes a collaborative recommendation method for extracting typical group preferences using user-item matrix optimization and user profiles in collaborative tittering systems. The method excludes unproven users by using entropy based on data from user-rated items and groups users into clusters after generating user profiles, and then extracts typical group preferences. The proposed method generates collaborative user profiles by using association word mining to reflect contents as well as preferences of items and groups users into clusters based on the profiles by using the vector space model and the K-means algorithm. To compensate for the shortcoming of providing recommendations using correlations between only two user preferences, the proposed method extracts typical preferences of groups using the entropy theory The typical preferences are extracted by combining user entropies with item preferences. The recommender system using typical group preferences solves the problem caused by recommendations based on preferences rated incorrectly by users and reduces time for retrieving the most similar users in groups.

• Journal of KIISE
• /
• v.43 no.5
• /
• pp.579-589
• /
• 2016

Currently, corporations have introduced the knowledge management system that utilizes knowledge effectively for practical purpose and development of core ability. However, existing knowledge systems have failed to share the knowledge content due to lack of elements that encourage the members to participate in the system. In this study, we designed a novel knowledge management system that employs the structure of social network service (SNS). More precisely, screen layout according to function and several algorithms to improve user friendliness and produce integrated knowledge content are recommended. The proposed SNS-based knowledge management system encourages the enterprise members to participate in the system to produce and share valuable knowledge contents.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.5
• /
• pp.43-52
• /
• 2013

In recent years, a large amount of music content is distributed in the Internet environment. In order to retrieve the music content effectively that user want, various studies have been carried out. Especially, it is also actively developing music recommendation system combining emotion model with MIR(Music Information Retrieval) studies. However, in these studies, there are several drawbacks. First, structure of emotion model that was used is simple. Second, because the emotion model has not designed for Korean language, there is limit to process the semantic of emotional words expressed with Korean. In this paper, through extending the existing emotion model, we propose a new emotion model KOREM(KORean Emotional Model) based on Korean. And also, we design and implement ontology using emotion model proposed. Through them, sorting, storage and retrieval of music content described with various emotional expression are available.

• Korean Journal of Soil Science and Fertilizer
• /
• v.27 no.2
• /
• pp.92-97
• /
• 1994

An attempt was made to provide the most resonable fertilizer recommendation for sesame and peanut crops based on soil analytical data and yield response to the NPK fertilizer application, which were obtained from field experiments conducted during 1970 to 1993. 1. According to the analytical data of sesame and peanut soils obtained in 1985~1993, the contents of organic matter, available $P_2O_5$, exchangeable K, Ca and Mg were increased in sesame soils, but the those components were decreased in peanut soils. 2. The yield index of the plot without N, $P_2O_5$ and $K_2O$ fertilizer were 81-84, 84~92 and 81~92, respectively, as the yield of NPK plot was regarded as 100. 3. Linear or quadratic equations derived from the relationship between soil analysis data and fertilizer application rates were proposed for NPK recommendation. The parameters of soil analysis used in the equations for N, P and K were organic matter, available $P_2O_5$ and exchangeable K, respectively. 4. Revised fertilizer recommendation based on the soil chemical status enable to save the fertilizer application of sesame and peanut soils. The amounts of saved NPK fertilizers were 5.1kg N/10a(increase in 2.8kg N/10a for peanut), 0.9~2.9kg $P_2O_5/10a$, and 1.7~5.8kg $K_2O$/10a.

• Asian Oncology Nursing
• /
• v.5 no.1
• /
• pp.11-21
• /
• 2005

The purpose of this study were to develop an web-based education program for Lung cancer patients and to test its effects on patients' self-care knowledge, compliance to medical regimen, nutrition status and pain. The program was developed by the following process: first, Lung cancer patients demand on the web-based program was investigated. and second, the program was developed with the help of various reference books and then validation of experts group. last, educations effects on the patients is evaluated and compared the differences in self-care knowledge, compliance to medical regimen, nutrition status and pain between on experimental group and a control group on before discharge 1day and 3weeks after. SPSS/Win 11.0 program was used for data analysis. It was proven with $x^2$ test and t-test, and Pearson Correlation coefficient, and Chronbach's alpha coefficient were done for the reliability of measuring instruments. 1. The summary of the Program development is as follows. The program is based on patients' questionnaire and reference material and is made for users friendly. Not only Bigger font size and bright colors but also illustrations or pictures were adopted to help enhance patients' understanding. 2. The summary of the study results is as follows. 1) Compared with control group, the web-based educated experimental group showed a statistical significant difference on self-care knowledge, Especially disease, radiation treatment, medication & analgesics, chemotherapy side effect, but there was no significant difference in the field of chemotherapy, in the fields of operation, diet & general knowledge. 2) Compared with control group, the web-based educated experimental group showed a statistical significant difference on compliance to medical regimen, especially in the field of follow up care, everyday life, diet, but there was no significant difference in the field of medication, exercise. 3) Compared with control group, web-based educated experimental group showed no significant difference in nutrition status, but partially significant difference in body weight. 4) Compared with control group, the web-based educated experimental group showed no significant difference in pain level. 5) The significantly positive correalation self-care knowledge with the compliance to medical regimen. 6) Users satisfaction with the web-based education program of the contents quality, the level of recommendation to others, content layout, medical information quality, but interesting got a low mark.