• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1681-1698
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• 2011

According to the demands of the times, Inchon international airport railroad opened up step by step but It is situation that much government subsidies are paid because It does not competitive power with road traffic by decline of schedule speed. Inchon international airport railroad users will convert by other transportation and minimize damage their time as travel time is prolonged. Therefore, need high speedization of airport railroad, this may act big role competitive power security as well as airport railroad activation with another public transportation. Thus, this paper suggests that a high speedization possibility section in the sections of airport railroad and train speed elevation effect analysis by roadbed, railroad, system improvement and the most efficient operation intervals analyzing each vehicles (AREX (120km/h), KTX (230km/h), EMU(Electric Multiple Unit, 180km/h) train running pattern.

• Information Systems Review
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• v.10 no.1
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• pp.213-235
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• 2008

Recent reports about economic structure and changes show that global economy changes to rely on service rather than manufacturing. This phenomenon can be explained in two ways: the growth of service industry itself and the increasing reliance on service by other industry areas. The importance of service is indicated by the fact that the contribution of research and development, marketing, and finance to the revenue generation of companies is getting greater than that of manufacturing. This change in the economic structure calls for researchers' attention on the importance of service and the service-based economy. In the service-based economy, firms are considered value proposition providers and consumers actual value creators so that the concept of co-value creation becomes a key thesis to study. However, there are a variety of definitions of service and diversified measurements of service anchored in the supplier-oriented understanding of service yet. This lack of understanding of the service and the economic paradigm change causes a lot of problems in the areas of service productivity, service quality, and service innovation. Even though a new movement called service science started and rigorously pursues the way of enhancing the understanding of the economic change and service productivity, there is no framework that provides a unified view about the new role of service, service productivity, service quality, and thus service innovation. This study proposes a unified framework to provide a structured view about service provision and to facilitate the research on service. The framework is built on the concepts from previous studies about service marketing and service science: service life cycle and service networks including value activity network, resource integrator network, and capability network. We hope this study can be used as the basis for future studies on service science.

• Science of Emotion and Sensibility
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• v.25 no.2
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• pp.71-78
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• 2022

This study investigates the recommendation for tax accounting services used in many companies. In particular, it aims to create guidelines for small businesses with fewer than 100 employees, which are relatively difficult to manage in terms of cost or time. We surveyed 100 corporate officials on basic business information, such as the number of employees, job titles, and business type, as well as the type of tax accounting service, the recommended score for the service, the reason for the score, and other opinions related to tax accounting services. In particular, the recommendation score seeks to obtain more effective results by using the Net Promoter Score method, which is known to be more effective in understanding customer opinions than general customer satisfaction surveys. The survey revealed a Net Promoter Score for a recommendation of -33 points, lower than the general Net Promoter Score. It also indicated that tax accounting services need improvement. Specifically, the opinions of the respondents who gave a non-recommendation score were as follows: "Not inconvenient or comfortable," "It was just okay," "I don't know if it would be helpful," and "There is no differentiation and there are no special alternatives." We concluded that an improved service for raising recommendation scores was necessary. This survey focused on recommendations for companies with fewer than 100 employees; future studies should incorporate larger companies and more variables.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1650-1654
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• 2007

홍수와 가뭄의 증가, 수질악화, 물부족 등 물 문제 해결을 위한 대안으로 통합수자원관리에 대한 논의가 국제사회에서 활발하게 진행되고 있다. 국내에서도 많은 학자들이 수자원관리를 위한 새로운 대안으로 통합수자원관리를 주장하고 있지만, 추상적인 설명이 대부분이다. 따라서 본 연구는 통합수자원관리에 대한 정의, 원칙, 추진전략 등을 정리하여 통합수자원관리에 대한 종합적이고 체계적인 정보를 제공하고자 한다. 본 연구는 다음과 같은 흐름을 갖는다. 첫째, 수자원관리를 위한 새로운 대안으로 통합수자원관리가 등장하게 된 배경을 살펴보았다. 물문제를 해결하기 위해서는 연속적이고 상호작용하는 하나의 '시스템(係)'으로 수자원을 인식하고 관리해야 한다는 주장이 확산되고 있으며, 통합수자원관리가 그러한 인식을 갖고 있는 대안으로 등장하였다. 둘째, 통합수자원관리의 정의, 원칙 등을 조사하였다. 통합수자원관리는 자연의 지속가능성을 훼손하지 않으면서 경제적, 사회적 복지를 최대화하기 위하여 물, 토지 및 관련 자원의 조화로운 개발을 위한 과정으로 정의된다. 이러한 통합수자원관리를 위한 원칙으로는 지속가능한 수자원의 개발, 이용 및 관리원칙, 물순환 체계 고려 및 유역관리원칙, 이해당사자 참여 및 조정의 원칙, 비용부담 및 편익 균형배분의 원칙 등이 있다. 셋째, 통합수자원관리를 위한 추진방안을 제시하였다. 법제도 정비 및 부문별 통합관리강화, 수자원 관련 자료의 신뢰도 제고 및 의사결정 체계 구축, 관련계획과의 연계, 계획-실행-평가의 순환구축, 물관리 비용부담체계 구축 등이 통합수자원관리의 실행을 앞당길 수 있을 것이다. 본 연구는 통합수자원관리에 대하여 종합적인 정보를 제공하고 개선을 위한 추진방안을 제시하여 국내 수자원관리의 문제해결을 위한 기반을 구축하는 데에 기여할 것으로 기대된다. 범람범위의 1차적인 정보에서 수립할 수 있었던 계획이 가질 수 있었던 한계점을 좀 더 향상된 정보를 이용하여 극복함으로써 효율적이고 체계적인 치수 방재 계획수립이 가능할 것으로 판단된다.group) 67개, 속(family) 161개로 분류되었으며, 가장 저차단위인 통(series)이 390개 분류되었다. 또한 작물이용측면에서 실용적 분류를 실시하였는데, 논토양의 경우 보통논, 미숙논, 사질논, 습논, 염해논, 특이산성논으로 분류할 경우 각각의 분포면적이 31.9%, 23.0%, 31.9%, 9.1%, 3.9%, 0.2%이었다. 밭토양의 경우에도 보통밭, 사질밭, 미숙밭, 중점밭, 고원밭, 화산회밭으로 6개 유형으로 분류할 경우 각각의 분포면적은 41.9%, 23.3%, 17.5%, 13.9%, 1.1. 2.2% 이었다. 도시화 및 도로확대 등 다양한 토지이용 및 지형개변으로 과거의 토양정보가 많이 변경되었다. 그래서, 앞으로는 인공위성자료 및 항공사진을 이용하여 빠르고 쉽게 활용할 수 있는 토양조사 방법개발과 기 구축된 토양도의 수정, 보완 작업이 필요한 절실히 요구되고 있는 현실이다.브로 출시에 따른 마케팅 및 고객관리와 관련된 시사점을 논의한다.는 교합면에서 2, 3, 4군이 1군에 비해 변연적합도가 높았으며 (p < 0.05), 인접면과 치은면에서는 군간 유의차를 보이지 않았다 이번 연구를 통하여 복합레진을 간헐적 광중합시킴으로써 변연적합도가 향상될 수 있음을 알 수 있었다.시장에 비해 주가가 비교적 안정적인 수준을 유지해 왔다고 볼 수 있다.36.4%)와 외식을 선호(29.1%)${\lrcorner}$ 하기 때문에 패스트푸드를 이용하게 된 것으로 응답 하였으며, 남 여 대학생간에는 유의한 차이(p<0.05)가 인정되었다. 응답자의 체형은 ${\

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.107-133
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• 2021

This study was performed in order to provide suggestions on how to strengthen librarian competency by evaluating and analyzing the competency value of librarians as information professions. First, the study divided the common competency value of librarians as human capital of libraries into skills, knowledge, behavior and attitude, and analyzed each area of competency value for librarians of the A-library. As a result, the average of the 'librarian's behavior and attitude' area was the highest, followed by the 'librarian's skill' area and the 'librarian's knowledge' area. Second, in terms of 'librarian's skill', A-library librarians' competence values were high in the order of 'communication', 'leadership', 'technology' and in the terms of 'librarian's knowledge' ones were high in the order of 'law and policy', 'marketing', 'learning and growth' and 'finance and accounting'. In addition, in areas of 'librarian's behavior and attitude', the factors were high in the order of 'ethics and values', 'interpersonal relationships' and 'customer service'. Third, the analysis of whether the average difference exists depending on the characteristics of A-library librarians on their evaluation of the competency value shows that only the 'working period' factor in the total competency value and the two factors 'age' and 'working period' were statistically significant in the 'librarian's knowledge' area. Forth, as a result of a regression analysis to identify the characteristics of A-library librarians and their impact on competency value, only the 'final education' factor was statistically significant for the competency value of the 'librarian's skill' area. Fifth, in the survey on problems and desirable improvement measures in increasing the competency value of librarians, the proportion of presenting problems and improvement plan in systemic aspects such as the 'librarian qualification system' and 'librarian training system' was high.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.184-193
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• 2020

The purposes of this paper are to find the effects of beauty shop online motivations on the convenience of reservation system, to investigate the convenience of reservation system on satisfaction, and to determine the effects of satisfaction on word-of-mouth behaviors. Based on the results, there are three factors in the motivations: diversion, service-prioritized, and impulse-driven tendencies. Also, there are five factors in the reservation convenience perception: efficiency of decision-making, easy monetary transaction, overall convenience, accessibility, and effortless nature of rewarding system. In terms of the convenience of online booking, the access convenience was found that as the motivation diversion and the service-prioritized motivation higher and as the impulse reservation motivation lower. Furthermore, this paper concludes that offered by online beauty service reservation systems, and higher satisfaction rate leads to higher review behaviours.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.