• Journal of Information Management
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• v.36 no.3
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• pp.127-165
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• 2005

This study is focused on the quality of the Web databases which has been produced in science. For the quality evaluation of NDSL, PubMed, Scopus, and WoS, 10 evaluating criteria are developed on the basis of literature review. The evaluation results show that NDSL and PubMed are superior in the currentness and cost. Scopus and WoS are superior in the information of citing and the analysis tool. It is needed for purchasing, user training, and library service based on the above evaluation results.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.591-597
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• 2016

Research question and method play important roles in conducting a research in a scientifically valid way. In today's digitalized research environment, social network service (SNS) has rapidly become a new source of big data. While this shift provides new challenges for researchers in Korea, there is little scholarly discussion of how research questions can be framed and what statistical methods can be applied. This article suggests some basic but primary types of example questions for researchers employing social big data analytics. Further, we illustrate the interface of the intended data set specifically for SNS-mediated communication and information exchange behaviors. Lastly, a statistical test known as proper method for social big data is introduced.

• Culinary science and hospitality research
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• v.6 no.1
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• pp.225-252
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• 2000

This study aims to examine theoretical frame work of franchise restaurant, the characteristics of store manager's job and the level of their job satisfaction through an empirical investigation. Job satisfaction survey study shows that store managers consider important all work to be attended to as part of their duty with service management on top. It is also found that the majority of store managers consider their aptitude as most important job satisfaction factor and those, who are satisfied with their job content, advancement and the prospect, are more proactive in delivering qualify service and more than willing to commit themselves to their duties. Regrading demographical variables, store managers with scholarly competence and higher pay level are more likely to be satisfied with their job but married men are not satisfied with the work environment in general. Ergo, Businesses should correspond by capitalizing on those store managers content with their duty thus collecting additional information and providing opportunities to further contribute to the business. For those dissatisfied individuals, however, businesses should determine their demands and by educational training supply a motive therefore making possible the conversion of such individuals to satisfied store managers and their active participation in business management. But, as with any study, this one has a number of limitation which constraints the generalizability of the empirical findings. It has not been for long since franchise restaurants established in domestic market and has been few studies regarding this topic there. Furthermore, managers are not willing to release operation related data. Therefore, further study are urged to overcome this limitation and should examine other dimensions of job satisfaction such as relations between revenue and profit with the level of store manager's job satisfaction remain to be investigated.

• Journal of Information Management
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• v.41 no.4
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• pp.227-249
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• 2010

Scholarly information has increased tremendously according to the development of IT, especially the Internet. However, simultaneously, people have to spend more time and exert more effort because of information overload. There have been many research efforts in the field of expert systems, data mining, and information retrieval, concerning a system that recommends user-expected information items through presumption. Recently, the hybrid system combining a content-based recommendation system and collaborative filtering or combining recommendation systems in other domains has been developed. In this paper we resolved the problem of the current recommendation system and suggested a new system combining collaborative filtering and Naive Bayes Classification. In this way, we resolved the over-specialization problem through collaborative filtering and lack of assessment information or recommendation of new contents through Naive Bayes Classification. For verification, we applied the new model in NDSL's paper service of KISTI, especially papers from journals about Sitology and Electronics, and witnessed high satisfaction from 4 experimental participants.

• Physical Therapy Korea
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• v.26 no.2
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• pp.34-48
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• 2019

Background: Fall-related injuries in older adults are a major health problem, and the risks and mechanisms of these injuries should be affected by race, culture, living environment, and/or economic status. Objects: Research articles have been systematically reviewed to understand fall-related injuries in older adults in South Korea. Methods: 128 published research papers have been found through the Korea Citation Index and the Korean Studies Information Service System, and reviewed in various perspectives, including incidents, fall death rates, medical costs, causes, injury sites and types, locations where falls occurred, prevention strategies, scholarly fields interested in fall injuries, and the role of physical therapy. Results: Fall-related injuries were found to be more common in women than in men, and the number of incidents increased with age, with the highest rate found in individuals over 85 years old. Risk of fall injury was associated with education level, comorbidities, and fear of falling. Common places where falls occurred included the bathroom, living room, stairs, and hallway. Common types of injury included bruises, fractures, and sprains in the lower extremities. Intervention strategies included exercise programs, education, and protective clothing. Scholarly fields interested in fall-related injuries in older adults included medicine, nursing, physical therapy, occupational therapy, physical education, pharmacology, oriental medicine, biomedical engineering, design, clothing, and textiles. Physical therapy intervention using proprioceptive neuromuscular facilitation has been used to improve one's balance. Conclusion: Any movement during the activities of daily living can lead to a fall. Physical therapists are highly educated to analyze human movements and should be involved in more research and practices to solve fall-related injuries in older adults.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.97-123
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• 2008

Subject specialized services are introduced in library environment in order to meet users' needs, which become more specialized, characterized, and personalized. This concept dates back to the 1960 in Korean scholarly research, and previous studies revealed that many libraries in Korea have provided this kind of subject specialized services to library users. This study aimed to consider appropriate directions of subject specialization in Korea. This study examined seven library cases the structure of which is organized by subject specialization. It tried to give a good grasp of background of building up the subject specialization system, current state of the service and its effects, problems and challenges of operating the system, recruitment and training issues of subject specialist librarians, their duties and tasks, and so on. Also Announcements of academic subject specialist positions in Korea are compared to in other countries such as United States, UK, and Canada in order to analyze the demand for subject specialist librarians.

• Journal of Information Management
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• v.43 no.4
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• pp.191-210
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• 2012

Scholarly science citation data is typically of large volume and consists of a variety of data. Moreover, the volume of data is increasing more and more. Therefore, there are some requirements to store and manage the data efficiently and Korea Institute of Science and Technology Information (KISTI) develops Korea Science Citation Database (KSCD) which manage and serve very large-volume of korea science technique information including citation data. However, current services based on KSCD are not enough for various users. Thus, it is important issue to offer a variety of services using KSCD. For example, if a user searches articles described by a specific author, then a user may want to find not only the articles cited by a certain author but also those articles that study similar topics. However, it is not always easy to provide these services with citation data. Therefore, this paper surveys studies about services using citation data in order to find approaches for better utilizing KSCD. Especially, this paper considers data mining techniques, because data mining is one of the main techniques to extracting semantic information from big data. Therefore, this paper discusses methods for utilizing large volume of KSCD based on data mining technique.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.489-498
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• 2012

This paper consists of two parts: In the first part, we describe our work to build hierarchical knowledge base of digital library patron's research interests and learning topics in various scholarly areas through analyzing well classified Electronic Theses and Dissertations (ETDs) of NDLTD Union catalog. Journal articles from ACM Transactions and conference web sites of computing areas also are added in the analysis to specialize computing fields. This hierarchical knowledge base would be a useful tool for many social computing and information service applications, such as personalization, recommender system, text mining, technology opportunity mining, information visualization, and so on. In the second part, we compare four grouping algorithms to select best one for our data mining researches by testing each one with the hierarchical knowledge base we described in the first part. From these two studies, we intent to show traditional verification methods for social community miming researches, based on interviewing and answering questionnaires, which are expensive, slow, and privacy threatening, can be replaced with systematic, consistent, fast, and privacy protecting methods by using our suggested hierarchical knowledge base.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.