• Journal of the Korean Society for Library and Information Science
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• v.41 no.4
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• pp.93-111
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• 2007

The Internet is now an integral part of the everyday lives of a majority of people. Web users are becoming increasingly skeptical of the information and services offered online. They are demanding web sites that offer credible information. This study focused on what features of web sites affect the perception of web credibility. For this purpose, I took the responses from 648 people and extracted 49 factors that affect web credibility. I placed the individual factors - the specific questions asked in the survey - into one of four categories expertise. trustworthiness, ads and other and calculated the means for each of the 49 factors. As a result, 29 out of 49 factors increase the Perceptions of credibility and 20 factors decrease the web credibility. Sites with frequently update. the credentials of authors, strict content guides, search capabilities, clear connections to the real world fared good in credibility. Technical problems such as broken links, site sown, or typographical errors were rated the most negative on this scale On the other end of the scale, a domain name that ends in' .org' or' .or.kr' caused little change in perception of credibility.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.209-231
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• 2015

The main purpose of this study is to develop and apply a means of connecting reading movement and Newspaper In Education (NIE) activities utilizing the voluntary participation and cooperation of local school districts and autonomous government entities. This is necessary to revitalize or systematize the environmental social life of reading newspapers and NIE activity. Literary or inquiry research will be initiated in this study in order to quantify the current or actual conditions of this connection, delineating the basic objectives of this study, and determining the developmental directions for continuing this study as related to the connection of reading movement and NIE activity. Anticipated study activities or major tasks are as follows. First, develop a variety of intended programs and learning materials necessary for each. Secondly, develop and establish corresponding online data and educational programs. Thirdly, a "cooperation" system must be established and training programs implemented reinforcing these ideas. And, lastly (and to gain wider acceptance), starting a public relations campaign to show or illustrate the benefits of this study and these intended research activities. In conclusion, if a connection between reading movement and NIE activity are fully established and periodically adjusted by means of continuing discussions on the merits or concerns based on the study findings, the full potential of the reading movement connection with NIE activity will be realized and achieved to its truest meaning and/or highest order.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.21-48
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• 2021

Today, with countless health information being accessible through online and offline, the public has been able to explore health-related information in various ways. The current study focuses on the information-seeking behavior of the mothers who actively explore information related to the health of their healthy infants (aged between 0 and 3 years). The researcher had conducted in-depth interviews of 24 American, Korean, and Korean immigrant mothers living in the United States, and then analyzed the sequential order of the information sources that they have used to search for the health-related information about their children. The current research highlights that the mothers' information-seeking pathways and searched topics tended to differ in accordance with their child(ren)'s health conditions (e.g., ill vs. healthy). For instance, regarding the information sources used, more diverse health information sources (e.g., public libraries, government health agencies, daycare teachers) were used when their child(ren) was not ill. In addition, when a child was ill, mothers were likely to focus on information about specific diseases or symptoms first, whereas when the child was healthy, they used to explore information on various health topics such as growth and development, nutrition and diets, parenting, and so on. Based on the results, implications for the information professionals are discussed when designing and providing health-related information services to mothers of healthy infants and toddlers.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.313-332
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• 2020

The purpose of this study is to compare motivations for self-archiving across disciplines on an academic social networking site. We carried out an online survey with ResearchGate(RG) users, testing 18 motivational factors that we developed from a previous study (enjoyment, personal/professional gain, reputation, learning, self-efficacy, altruism, reciprocity, trust, community interest, social engagement, publicity, accessibility, self-archiving culture, influence of external actors, credibility, system stability, copyright concerns, additional time, and effort). We adapted Biglan's classification system of academic disciplines and compared motivations across different categories of discipline. First, we compared motivations across the four combined categories by the two dimensions - hard-pure, hard-applied, soft-pure, and soft-applied. We also performed a motivation comparison across each dimension between soft and hard disciplines and between pure and applied disciplines. We examined investigated statistical differences in motivations by demographic characteristics and RG usage of participants across categories as well. Findings showed that there were differences of motivations, such as enjoyment, accessibility, influence of external actors and additional time and effort, and personal/professional gains, for self-archiving across disciplines. For example, RG users in the hard-applied were more highly motivated by enjoyment than others; RG users in the soft-pure were more highly motivated by personal/professional gains than others. It is expected that findings could be used to develop strategies encouraging researchers in various disciplines contributing to share their data and publications in ASNSs.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.255-283
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• 2024

In this study, as a preliminary research to effectively support data-driven R&D of researchers, we analyzed the academic information and data requirements for researchers to discover new types of academic information and datasets, and to propose directions for academic information services. To achieve the research objectives, we conducted an exploratory case study involving five researchers and administered an online survey among ScienceON users to glean insights into data-driven R&D behaviors and information/data requirements. As a result, researchers relatively referred to academic papers, datasets and software information from academic papers or conference materials. Moreover, the methods and pathways for acquiring data, as well as the types of data, varied across different subject areas. Researchers often faced challenges in data-driven R&D due to difficulties in locating and accessing necessary datasets or software such as learning models. Therefore it has been analyzed that for future support of data-driven R&D, there is a need to systematically construct datasets by subject. Additionally, it is considered necessary to extract and summarize dataset and related software information in conjunction with academic papers.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.6997-7002
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• 2015

Background: In cervical cancer patients it has been reported that there in a significant Ki-67/MIB-1 expression is correlated with survival in cervical cancer patients. However, the prognostic value is still not well understood. Materials and Methods: In the present meta-analysis the prognostic value of Ki-67/MIB-1 with regard to overall survival (OS) and disease-free survival (DFS) in cervical cancer was investigated. The databases of PubMed, ISI Web of Science, Cochrane Central Register of Controlled Trials, EMBASE, Science Direct and Wiley Online Library were used to identify appropriate literature. Results: In order to explore the relationship between Ki-67/MIB-1 and cervical cancer, we have included 13 studies covering 894 patients in the current meta-analysis. The effect of Ki-67/MIB-1 on OS for pooled random effects HR estimate was 1.63 (95%confidence interval (CI) 1.09-2.45; P<0.05). The pooled HR for DFS was 1.26 (95%CI 0.58-2.73; P>0.05) and the subgroup analysis indicated Ki-67/MIB1 was associated with DFS (HR=3.67, 95%CI 2.65-5.09) in Asians. Conclusions: According to this meta-analysis, Ki-67/MIB-1 has prognostic value for OS in patients suffering from cervical cancer. For better evaluation of the prognostic role of Ki-67/MIB-1 on DFS, studies with larger numbers of patients are needed to validate present findings in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1183-1188
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• 2016

Kinect sensor version 2 is a kind of camera released by Microsoft as a computer vision and a natural user interface for game consoles like Xbox one. It allows acquiring color images, depth images, audio input and skeletal data with a high frame rate. In this paper, using depth image, we present a surveillance system of a certain area within Kinect's field of view. With computer vision library(Emgu CV), if an object is detected in the target area, it is tracked and kinect camera takes RGB image to send it in database server. Therefore, a mobile application on android platform was developed in order to notify the user that Kinect has sensed strange motion in the target region and display the RGB image of the scene. User gets the notification in real-time to react in the best way in the case of valuable things in monitored area or other cases related to a reserved zone.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2499-2506
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• 2016

Background: Gastric cancer (GC) is the second leading cause of cancer-related death worldwide. Several environmental, genetic and epigenetic factors have been suggested to have a role in GC development. Epigenetic mechanisms like histone changes and promoter hyper-methylation are now being increasingly studied. Associations between methylation of many gene promoters with the risk of gastric cancer have been investigated worldwide. Such aberrant methylation may result in silencing of specific genes related to cell cycling, cell adhesion, apoptosis and DNA repair. Thus this molecular mechanism might have a key role in proliferation and migration of cancerous cells. Materials and Methods: In this review article we included studies conducted on DNA methylation and gastric cancer in Iranian populations. Using Science direct, Pubmed/PMC, Springer, Wiley online library and SciELO databases, all published data until 31 January 2016 were gathered. We also searched Science direct data base for similar investigations around the world to make a comparison between Iran and other countries. Results: By searching these databases, we found that the association between methylation of seven gene promoters and gastric cancer had been studied in Iran until 31 January 2016. These genes were p16, hLMH1, E-cadherin, CTLA4, $THR{\beta}$, mir9 and APC. Searching in science direct database also showed that 92 articles had been published around the world till January 2016. Our investigation revealed that despite the importance of GC and its high prevalence in Iran, the methylation status of only a few gene promoters has been studied so far. More studies with higher sample numbers are needed to reveal the relation of methylation status of gene promoters to gastric cancer in Iran. Conclusions: Further studies will be helpful in identifying associations of DNA methylation in candidate genes with gastric cancer risk in Iranian populations.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.440-445
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• 2017

Due to the advance of e-commerce systems, the number of people using online shopping and products has significantly increased. Therefore, the need for an accurate recommendation system is becoming increasingly more important. Recurrent neural network is a deep-learning algorithm that utilizes sequential information in training. In this paper, an evaluation is performed on the application of recurrent neural networks to recommendation systems. We evaluated three recurrent algorithms (RNN, LSTM and GRU) and three optimal algorithms(Adagrad, RMSProp and Adam) which are commonly used. In the experiments, we used the TensorFlow open source library produced by Google and e-commerce session data from RecSys Challenge 2015. The results using the optimal hyperparameters found in this study are compared with those of RecSys Challenge 2015 participants.