• The Journal of the Korea Contents Association
• /
• v.15 no.8
• /
• pp.37-45
• /
• 2015

With advancement in information technologies and a better mobile environment, the paradigm of service is shifting again from web portals to networked-applications based on individual application programs. Furthermore, as more investment is being made in R&D, the efforts to enhance R&D productivity are becoming important. In this paper, we designed a personalized service model for developing a tool to assist researchers in their R&D activities. To do this, we first compared services and tools in terms of information activities of researchers in R&D. In addition, we also analyzed changes of information environment such as open expansion of information and data, enhancement of personal information protection, popularization of social networking service, very big contents, advances in web platform technology in terms of personalization, and defined some directions of developing a personalized service. Subsequently we designed a personalized service model of research support tool in the views of functions, contents, operation, and defined personalized design goals and principles for implementing it as standard, participation, and open.

• Management & Information Systems Review
• /
• v.35 no.3
• /
• pp.273-287
• /
• 2016

This study aimed to clarify the effect of information technology (IT) education on the efficiency and effectiveness of working processes among agriculture corporations. Survey data on information levels from 222 agriculture corporations were collected from the Korean Agency of Education, Promotion, and Information Service in Food, Agriculture, Forestry, and Fisheries (EPIS) for a governmental white paper. Structural equation modeling was used for analysis. This study found that IT education increases the ratio of the use of information systems in working processes, especially given the use of data accumulated through information and communications technologies (ICT). The findings of this study suggest that the use of ICT data as an aspect of IT education is beneficial for the agricultural sector.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.23 no.1
• /
• pp.97-107
• /
• 2013

The recent increase in smartphone usage has ignited the development of new applications which have changed the way of living in this internet era in the world. Almost all users which have smartphone have used many kinds of applications for lots of part. Especially, Social Network Service is the most popular part for smartphone users. The greater part of smartphone users take messenger service for smartphone. This kinds of applications provide to manage as deactivation of user or change of device. When users take to manage their information, their information would be deleted securely. If secure deletion didn't work correctly and released, their personal information can be easily abused to by others through various means such as internet phishing. In this paper, we analysis that the messenger application's management function keeps on the Personal Information Protection Act and suggest to prevent legally and technically for user's personal information and privacy.

• Journal of Internet Computing and Services
• /
• v.13 no.5
• /
• pp.33-43
• /
• 2012

Semantic web is utilized to construct advanced information service by using semantic relationships between entities. Text mining can be applied to generate semantic relationships from unstructured data resources. In this study, ontology schema guideline, ontology instance generation, disambiguation of same name by text mining and advanced historical people finding service by reasoning have been proposed. Various relationships between historical event, organization, people, which are created by domain experts, are linked to literatures of National Institute of Korean History (NIKH). It improves the effectiveness of user access and proposes advanced people finding service based on relationships. In order to distinguish between people with the same name, we compares the structure and edge, nodes of personal social network. To provide additional information, external resources including thesaurus and web are linked to all of internal related resources as well.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.7-12
• /
• 2016

DRAM is commonly used as a smartphone memory medium, but extending its capacity is challenging due to DRAM's large battery consumption and density limit. Meanwhile, smartphone applications such as social network services need increasingly large memory, resulting in long latency due to additional storage accesses. To alleviate this situation, we adopt emerging nonvolatile memory (NVRAM) as smartphone's buffer cache and propose an efficient management scheme. The proposed scheme stores all dirty data in NVRAM, thereby reducing the number of storage accesses. Moreover, it separately exploits read and write histories of data accesses, leading to more efficient management of volatile and nonvolatile buffer caches, respectively. Trace-driven simulations show that the proposed scheme improves I/O performances significantly.

• The KIPS Transactions:PartD
• /
• v.19D no.1
• /
• pp.113-120
• /
• 2012

Today, Internet users can easily create and share the digital contents with others through various online content sharing services such as YouTube. So, many portal sites are flooded with lots of user created contents (UCC) in various media such as texts and videos. Estimating popularity of UCC is a crucial concern to both users and the site administrators. This paper proposes a method to predict the popularity of Internet articles, a kind of UCC, using the dynamics of the online contents themselves. To analyze the dynamics, we regarded the access counts of Internet posts as the popularity of them and analyzed the variation of the access counts. We derived a model to predict the popularity of a post represented by the time series of access counts, which is based on an exponential function. According to the experimental results, the difference between the actual access counts and the predicted ones is not more than 10 for 20,532 posts, which cover about 90.7% of the test set.

• Journal of Digital Convergence
• /
• v.11 no.1
• /
• pp.423-430
• /
• 2013

The development of information technology introduced digital contents and Social Network Services(SNS), and allowed the virtual transaction and communication between users called "the experience knowledge" advanced from "the objective knowledge." This paper will analyze interactive storytelling system creating different types of stories on narrative genre about family history, personal history and so on. Through analysis on narrative interviews, direct observations, documentations and visual records, contents about CEO story, corporate story, family story and especially family history will be categorized into sampleDB and informationDB. Accumulated contents will allow the user to increase the value and usage of the contents through interactive storytelling system by restructuring the contents on family history. This research has developed writing tool data model using different digital contents such as texts, images and pictures to encourage open communications between first generations and third generations in Korea. Furthermore, researched about connected system on interactive storytelling creation device using various genre of family story that has been data based.

• Journal of Korean Society of Rural Planning
• /
• v.27 no.4
• /
• pp.43-54
• /
• 2021

This study analysed changes in rural tourism between before and after COVID-19 using LDA topic analysis. In order to understand the changes in rural tourism, blog data including the keyword 'Gochang-gun travel' was used. As a result of LDA topic analysis with blog data retrieved, the study found nine topics in 2019 and 2020. 2019 and 2020 are, generally, consistent in topics, but the three topics related to rural experiential tourism that appeared in 2019 did not appear in 2020. In 2020, three new topics emerged: Beach vacations and campings. New travel activities of noncontact with other people(Untact tourism in Korean context) in the COVID-19 era, and The negative impacts on travel businesses and behaviours from COVID-19. Especially, the adverse effects of COVID-19 have made an enormous decline in rural experience tourism destinations and cancellation of local festivals. On the other hand, new tourism activities have emerged due to COVID-19. Those activities have included camping, drive-thru destinations, and cycling. Ecological and natural tourist sites such as Ungok Wetland, Seonunsan Mountain, Seonunsa Temple, and Gusipo Beach appeared. These tourist destinations have a quiet atmosphere and less density place noncontacting with other people when visiting. Also, because overseas travel has become difficult, long-term stay travel in rural areas has appeared. This study indicates that COVID-19 has less impacted rural tourism than other tourism destinations with these positive and negative impacts.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.45 no.4
• /
• pp.104-117
• /
• 2017

This study compares the results of landscape image analysis using text mining techniques and factor analysis for Lotte World Tower, which is the first atypical skyscraper building in Korea, and identifies landscape images of the site to determine possibilities of use. Lotte World Tower's landscape image has been extracted from text mining analysis focusing on adjectives such as 'new', 'transformational', 'unusual', 'novelty', 'impressive', and 'unique', and phrases such as in the process of change, people's active elements(caliber, outing, project, night view), media(newspaper, blog), and climate(weather, season). As a result of the factor analysis, factors affecting the landscape image of Lotte World Tower were symbolic, aesthetic, and formative. Identification, which is a morphological feature, has characteristics of scale and visibility but it is not statistically significant in preference. Rather, the psychological factors such as the symbolism with characteristics such as poison and specialty, harmony with the characteristics of the surrounding environment, and beautiful aesthetic characteristics were an influence on the landscape image. The common results of the two research methods show that psychological characteristics such as factors that can represent and represent the city affect the landscape image more greatly than the morphological and physical characteristics such as location and location of the building. In addition, the text mining technique can identify nouns and adjectives corresponding to the images that people see and feel, and confirms the relationship between the derived keywords, so that it can focus the process of forming the landscape image and further the image of the city. It would appear to be a suitable method to complement the limitation of landscape research. This study is meaningful in that it confirms the possibility that big data can be utilized in landscape analysis, which is one research field of landscape architecture, and is significant for understanding the information of a big data base and contribute to enlarging the landscape research area.

• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.1-27
• /
• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.