• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.338-341
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• 2003

According to a long-term master plan for the implementing of MOMAF's marine environmental informatization, we have developed marine environment portal web site which consists of 7 main-menu and 39 sub-menu including various types of contents (text, image and multimedia) based on RDBMS. This portal site was opened in Oct., 2002 (http://www.meps.info). Also, for the national institutions' distributed DB which is archived and managed respectively the marine chemical data and biological data, the integrated retrieval system was developed. This system is meaningful for the making collaborative use of real data and could be applied for data mining, marine research, marine environmental GIS and making-decisions.

• The KIPS Transactions:PartA
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• v.11A no.2
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• pp.213-222
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• 2004

Today's Web-based teaching-learning is developing in the direction that learners select and organize the contents, time and order of learning by themselves. That is, it is evolving to provide teaching-learning environment adaptive to individual learners' characteristics(their level of knowledge, pattern of study. areas of interest). This study analyzed learners' learning paths among the variables of learners' characteristics considered important in Web-based teaching- learning process using the Apriori algorithm and grouped learners who had similar learning paths. Based on the result, the author designed and developed a learning-path individualization system In order to provide learners with learning paths, Interface, the progress of learning etc. The proposed system is expected to provide optimal learning environment fit for learners' pattern of study and to be enhancing individual learner's learning effects

• 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.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.229-249
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• 2016

This study was conducted to create a digital archive for local cultural contents compiled from the records of westerners who stayed in Korea during the Enlightenment Period of Chosun. The compiled information were gathered from 22 records, and 10 main subjects, 40 sub-subjects and 239 mini-subjects were derived through the subject classification scheme. Item analysis was conducted through 38 metadata and input data types were classified and databased in Excel. Finally, a web-based digital archiving system was developed for searching and providing information through various access points. Suggestions for future research were made to expand archive contents through continuous excavation of westerners' records, to build an integrated information system of Korean digital archives incorporating individual archive systems, to develop standardization of classification schemes and a multidimensional classification system considering facet structure in cultural heritage areas, to keep consistency of contents through standardization of metadata format, and to build ontology using semantic search functions and data mining functions.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.61-76
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• 2018

Everything is coming into the world of network where modern people are living. The Internet of Things that attach sensors to objects allows real-time data transfer to and from the network. Mobile devices, essential for modern humans, play an important role in keeping all traces of everyday life in real time. Through the social network services, information acquisition activities and communication activities are left in a huge network in real time. From the business point of view, customer needs analysis begins with SNS data. In this research, we want to build an automatic collection system of SNS contents of web environment in real time using Python. We want to help customers' needs analysis through the typical data collection system of Instagram, Twitter, and YouTube, which has a large number of users worldwide. It is stored in database through the exploitation process and NLP process by using the virtual web browser in the Python web server environment. According to the results of this study, we want to conduct service through the site, the desired data is automatically collected by the search function and the netizen's response can be confirmed in real time. Through time series data analysis. Also, since the search was performed within 5 seconds of the execution result, the advantage of the proposed algorithm is confirmed.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.111-121
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• 2009

In this paper, we propose a multimedia recommender system using user's playback time. Proposed system collects multimedia content which is requested by user and its user‘s playback time, as web log data. The system predicts playback time.based preference level and related contents from collected transaction database by fuzzy association rule mining. Proposed method has a merit which sorts recommendation list according to preference without user’s custom preference data, and prevents a false preference. As an experimental result, we confirm that proposed system discovers useful rules and applies them to recommender system from a transaction which doesn‘t include custom preferences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2571-2586
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• 2022

The rapid popularity of government social media has generated huge amounts of text data, and the analysis of these data has gradually become the focus of digital government research. This study uses Python language to analyze the big data of the Chinese provincial government Weibo. First, this study uses a web crawler approach to collect and statistically describe over 360,000 data from 31 provincial government microblogs in China, covering the period from January 2018 to April 2022. Second, a word separation engine is constructed and these text data are analyzed using word cloud word frequencies as well as semantic relationships. Finally, the text data were analyzed for sentiment using natural language processing methods, and the text topics were studied using LDA algorithm. The results of this study show that, first, the number and scale of posts on the Chinese government Weibo have grown rapidly. Second, government Weibo has certain social attributes, and the epidemics, people's livelihood, and services have become the focus of government Weibo. Third, the contents of government Weibo account for more than 30% of negative sentiments. The classified topics show that the epidemics and epidemic prevention and control overshadowed the other topics, which inhibits the diversification of government Weibo.

• The Journal of Information Systems
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• v.32 no.2
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• pp.177-190
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• 2023

Purpose Recently, as a new business marketing tool, short form content focused on fun and interest has been shared as hashtags. By extracting positive and negative keywords from media audiences through comment analysis of social media news, various stakeholders aim to quickly and easily grasp users' opinions on major news. Design/methodology/approach YouTube videos were searched using the YouTube Data API and the results were collected. Video comments were crawled and implemented as HTML elements, and the collection results were checked on the web page. The collected data consisted of video thumbnails, titles, contents, and comments. Comments were word tokenized with the R program, comparing positive and negative dictionaries, and then quantifying polarity. In addition, social network analysis was conducted using divided positive and negative comments, and the results of centrality analysis and visualization were confirmed. Findings Social media users' opinions on issue news were confirmed by analyzing and visualizing the centrality of keywords through social network analysis by dividing comments into positive and negative. As a result of the analysis, it was found that negative objective reviews had the highest effect on information usefulness. In this way, previous studies have been reaffirmed that online negative information has a strong effect on personal decision-making. Corporate marketers will analyze user comments on social network services (SNS) to detect negative opinions about products or corporate images, which will serve as an opportunity to satisfy customers' needs.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.533-542
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• 2011

Visualization elements as the technology to offer information to users effectively have become more important. In this study, we evaluate the usefulness of visualization elements in InSciTe which is a technology intelligence service developed by using Semantic Web technologies and text mining technologies for establishing R&D strategy using papers and patents. We propose design which can be preferred by users and applying methods of visualization elements through the quantitative and qualitative evaluation about each types of service. As a result of evaluation, we conclude that the visualization elements in InSciTe are implemented user-friendly to improve user's cognitive intuition.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.25-34
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• 2020

Community question and answering service is one of the main sources of information and knowledge in the Web. The quality of information in question and answer documents is determined by the clarity of the question and the relevance of the answers, and the readability of a document is a key factor for evaluating the quality. This study is to measure the quality of documents used in community question and answering service. For this purpose, we compare the frequency of occurrence by vocabulary level used in community documents and measure the readability index of documents by institution of author. To measure the readability index, we used the Dale-Chall formula which is calculated by vocabulary level and sentence length. The results show that the vocabulary used in the answers is more difficult than in the questions and the sentence length is longer. The gap in readability between questions and answers is also found by writing institution. The results of this study can be used as basic data for improving online counseling services.