• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.45-52
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• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.373-383
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• 2015

Spatial information has been widely used for efficient land use and management, disaster management, environment management, infrastructure management, corporate marketing, and cultural assets management, and the need for spatial information is expected to be increased. For this reason, central government, local government and public institutions must establish a National Spatial Information System (Fifteen systems related to spatial information managed by National Spatial Data Infrastructure Policy office, NSIS) framework that guarantees high accuracy and quality. The NSIS will provide convenience usage of spatial information in the field of decision-making or civil support. However the current National Spatial Information System is mainly established with separate processes, which causes data redundancy, deterioration of information, passive opening, and sharing of the spatial data. This study suggests 4 standards, which has been derived by applying value-chain model to NSIS data flow, and they are ‘Production and Establishment’, ‘Integration and Sharing’, ‘Application and Fusion’ and ‘Release and Opening’. Based on these standards, the 15 NSIS were analyzed to draw out implications and reforming directions were suggested. By following these suggestions we expect more recent, consist, accurate, and connected National Spatial Information Service which will be more open to public and then satisfy the demands.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.95-104
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• 2017

As the technology in smart device is growing and Social Network Services(SNS) are becoming more common, the data which is difficult to be processed by existing RDBMS are increasing. As a result of this, NoSQL databases are getting popular as an alternative for processing massive and unstructured data generated in real time. The demand for the technique of digital investigation of NoSQL databases is increasing as the businesses introducing NoSQL database in their system are increasing, although the technique of digital investigation of databases has been researched centered on RDMBS. New techniques of digital forensic investigation are needed as NoSQL Database has no schema to normalize and the storage method differs depending on the type of database and operation environment. Research on document-based database of NoSQL has been done but it is not applicable as itself to other types of NoSQL Database. Therefore, the way of operation and data model, grasp of operation environment, collection and analysis of artifacts and recovery technique of deleted data in HBase which is a NoSQL column-based database are presented in this paper. Also the proposed technique of digital forensic investigation to HBase is verified by an experimental scenario.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.75-82
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• 2015

Major corporations and portals have implemented a link server that connects Content Management Systems (CMS) to the physical address of content in a database (DB) to support efficient content use in web-based environments. In particular, a link server automatically connects the physical address of content in a DB to the content URL shown through a web browser screen, and re-connects the URL and the physical address when either is modified. In recent years, the number of users of digital content over the web has increased significantly because of the advent of the Big Data environment, which has also increased the number of link validity checks that should be performed in a CMS and a link server. If the link validity check is performed through an existing URL-based sequential method instead of petabyte or even etabyte environments, the identification rate of dead links decreases because of the degradation of validity check performance; moreover, frequent link checks add a large amount of workload to the DB. Hence, this study is aimed at providing a link server that can recognize URL link deletion or addition through analysis on the B-tree-based Information Identifier count per interval based on a large amount of URLs in order to resolve the existing problems. Through this study, the dead link check that is faster and adds lower loads than the existing method can be performed.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter 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. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.311-328
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• 2022

Because of the spread of smartphones due to the development of information and communication technology, online shopping mall services can be used on computers and mobile devices. As a result, the number of users using the online shopping mall service increases rapidly, and the types of products traded are also growing. Therefore, to maximize profits, companies need to provide information that may interest users. To this end, the recommendation system presents necessary information or products to the user based on the user's past behavioral data or behavioral purchase records. Representative overseas companies that currently provide recommendation services include Netflix, Amazon, and YouTube. These companies support users' purchase decisions by recommending products to users using ratings, purchase records, and clickstream data that users give to the items. In addition, users refer to the ratings left by other users about the product before buying a product. Most users tend to provide ratings only to products they are satisfied with, and the higher the rating, the higher the purchase intention. And recently, e-commerce sites have provided users with the ability to vote on whether product reviews are helpful. Through this, the user makes a purchase decision by referring to reviews and ratings of products judged to be beneficial. Therefore, in this study, the correlation between the product rating and the helpful information of the review is identified. The valuable data of the evaluation is reflected in the recommendation system to check the recommendation performance. In addition, we want to compare the results of skipping all the ratings in the traditional collaborative filtering technique with the recommended performance results that reflect only the 4 and 5 ratings. For this purpose, electronic product data collected from Amazon was used in this study, and the experimental results confirmed a correlation between ratings and review usefulness information. In addition, as a result of comparing the recommendation performance by reflecting all the ratings and only the 4 and 5 points in the recommendation system, the recommendation performance of remembering only the 4 and 5 points in the recommendation system was higher. In addition, as a result of reflecting review usefulness information in the recommendation system, it was confirmed that the more valuable the review, the higher the recommendation performance. Therefore, these experimental results are expected to improve the performance of personalized recommendation services in the future and provide implications for e-commerce sites.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.462-480
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• 2010

Patent analysis is the extracting knowledge which is needed for the company's research and development strategy through accumulated worldwide patent database. In order to set the future direction of corresponding technology which is scheduled to be developed, the technology trends and deployment processes are identified by analyzing results of present patent applications. The patent analysis provides the required results for analyzing present patent applications. In this paper, we will carry out technology classification for related patent analysis methods and systems. Moreover we will investigate and analyze related domestic patents, U.S. patents and IEEE papers. Due to the characteristics of technology sector, not only patents are applied but also research papers are released actively about patent analysis system. We will analyze patents according to the technology classification by using the final searching results which come from the selected search words in this study. To find necessary niche technology which is needed for patent analysis system, matrix analysis was performed to all of valid patents and papers. Identifying the technology development trends of registered patent analysis systems, and presenting the future direction of technology development which is related to patent analysis system. To figure out the technology which is developed relatively weak based on domestic patents, U.S patent and research papers by analyzing the valid patents and papers with statistical test and self-organizing map quantitatively. Then, presenting the necessity of this technology development.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.45-59
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• 2015

As many companies have been interested in big data, they have invested a lot of resources to get more customer data. Some companies try to trade the data illegally. In order to collect more customer data, companies provide various incentive programs to customers. However, their results are normally much less than their expectations. This study focuses on exploring the relative importance of the factors which influence customer attitudes to providing his/her personal information. This study conducts a conjoint analysis to assess trade-offs among the five influential factors-monetary reward, concern for data collection, concern for secondary use, concern for unauthorized use, and concern for errors. This study finds that the customer attitude to providing personal information is most influenced by the concern for secondary use. Furthermore, it shows that there are some differences between the light internet user group and the heavy internet user group in the relative importances of these factors. The monetary rewards appeal to the heavy internet users, rather than the light internet users.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.231-240
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• 2020

In this study, the case of OO corporation was based on to examine the business performance and method of OO corporation and the competitive advantage and success factors were considered. For the progress of this study, references and advanced researches related to entrepreneurship, authentic leadership, and organizational effectiveness, which were suggested as the core competence of non-profit organizations, were examined and textual information was secured through the homepage of the targeted organization and news articles. Lastly, data needed for the research was collected through an interview with the Chief Executive Officer (CEO) of the organization. Through the process and analysis, the following findings were identified. First, the entrepreneurship of the CEO can apply as a core competence for the operation of the non-profit organization. Second, the proposition was derived that the roles of the CEO and leadership can apply as a key competence in the operation of the non-profit organization. This study implies that the many theories and strategies which were only targeted on companies can also be applied for the research of non-profit organizations. Moreover, concerning modern corporate management, strategic approach of non-profit organization characteristics like a sense of mission, fairness, and ethics can promote the creation of sustainable competitive advantage.