• Journal of Digital Contents Society
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• v.6 no.1
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• pp.55-62
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• 2005

In this paper, we propose the new technique to compute the optimal route by considering the direction of distribution vehicles and the location for delivery, developing the algorithm of the shortest route to approach the location as applying the gemetic algorithm. This approach makes it possible for us to find the best route even under itineraries which include many destinations. Lively studies are currently in progress on the development of vehicle navigation software, combining PDA GPS, and electronic maps. Many web-sites are providing a varier of services which use electronic maps. Popular among these services is one that computes the optimal route between two positions that a user inputs. This service of computing the optimal route plays an important role in distribution industries such as home-delivery. For the distribution system. the construction of a vehicle regulation system enables us to calculate and manipulate the optimal route for distribution vehicles, to enhance the efficiency in making use of vehicles and labor, and to reduce costs.

• Journal of Korean Library and Information Science Society
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• v.48 no.1
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• pp.161-189
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• 2017

The purpose of this study is to describe the experience of visually impaired academic researchers' use of scholarly contents and to explore intrinsic nature of the experience. In-depth interview was conducted with a total number of twelve visually impaired academic researchers and the data were analyzed using Colaizzi's phenomenological research method. A total of 107 significant statements were extracted, divided into 44 themes and 12 theme clusters. The statements were then classified into four categories. The 'scholarly contents acquisition and use' category has to do with difficulties that these experience when negotiating with internet sites with poor web accessibility and full-text availability. The 'changes in perception and emotions' category deals with transitions in perception and mood experienced by visually impaired academic researchers' over time. The 'relationships with support personnel' category includes issues related with the difficulty of securing support person, support person's inadequate level of competence, and establishing/sustaining personal relationships. Finally, the 'improvement requirements' category includes issues that these researchers want resolved with regard to contents acquisition and use.

• Journal of Information Technology and Architecture
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• v.9 no.3
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• pp.333-344
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• 2012

This paper proposes a system which recommends movies using information from social network services containing personal interest and taste. Method for establishing data is as follows. The system gathers movies' information from web sites and user's information from social network services such as Facebook and twitter. The data from social network services is categorized into six steps of emotion level for more accurate processing following users' emotional states. Gathered data will be established into vector space model which is ideal for analyzing and deducing the information with the system which is suggested in this paper. The existing similarity measurement method for movie recommendation is presentation of vector information about emotion level and similarity measuring method on the coordinates using Cosine measure. The deducing method suggested in this paper is two-phase arithmetic operation as follows. First, using general cosine measurement, the system establishes movies list. Second, using similarity measurement, system decides recommendable movie list by vector operation from the coordinates. After Comparative Experimental Study on the previous recommendation systems and new one, it turned out the new system from this study is more helpful than existing systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.829-832
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• 2006

The word P2P implies significant changes in current business dynamics. The P2P service enables individuals to be connected to the Internet for the direct provision of information and even downloads from one another without the conventional method of passing through search engines. This can be utilized to extend the path of retrieving information from limited web sites to personal and enterprise databases. That is, it is now possible for individuals to manage their own information on a national or global scope, share various information with other members, form communities of users interested in sharing homogeneous information, and utilize remote conference and remote education using groupware.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.283-293
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• 2012

A new type of malware that extracts personal and account data over an extended period of time and that apparently is resistant to detection by vaccines has been identified. Generally, a malware is installed on a computer through network-to-network connections by utilizing Web vulnerabilities that contain injection, XSS, broken authentication and session management, or insecure direct-object references, among others. After the malware executes registration of an arbitrary service and an arbitrary process on a computer, it then periodically communicates the collected confidential information to a hacker. This paper is a systematic approach to analyzing a new type of malware called "winweng," a kind of worm that frequently made appearances during the first half of 2011. The research describes how the malware came to be in circulation, how it infects computers, how its operations expose its existence and suggests improvements in responses and countermeasures. Keywords: Malware, Worm, Winweng, SNORT.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.255-267
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• 2012

High Internet usage and the public's keen interest on health have influenced the health care system, and a potential value of the online health information and medical consultation market is immense. This study reveals results from data collected from Seoul residents in the age group of 20s in 2011. Out of 499 respondents, 75.2% answered that they used online health information; however, only 7.2% answered that they have used online medical consultation services. Findings on the purposes of using online medical consultation included treatments of symptoms(33.6%) and self-disciplines of one's health(19.5%). Mostly used Websites for health information search included search engines and blogs, but respondents preferred to use government sites and hospital sites in the future. When choosing a medical consultation, respondents preferred a certain website for different reasons including creditability of the consultant(23.7%), creditability of the organization(23.7%), rapid responses(21.2%), and more. Overall, although health information search via web is being highly utilized among people in their 20s, utilization of online medical consulting is not. Thus, promotion efforts to increase awareness and utilization of online medical consulting based on the site selection criteria, type of personal information disclosure, and other preferences are essential. Also, creating websites meeting these criteria is important.

• Informatization Policy
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• v.18 no.3
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• pp.25-49
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• 2011

As a way to gather diverse information required for everyday living, the importance of social networks has been growing. Social network services have been spreading rapidly because of diffusion of the Internet, evolution of social network sites, and recognition of the importance of social networks. Recently, the social network service has been evolved based on a new paradigm, Web 2.0, pursuing participation and openness. Following the adoption of Web 2.0 technologies, the social network service allows users to make and maintain new relationships in a more convenient way. Users of the social network service tend to reveal their personal information, and share their ideas and content with other people; in the process they become aware of their existence, feel satisfaction with life and exert influence to others as a member of the society. This study uses higher order factor analysis to analyze factors that affect the intention of using the social network service. A research model was developed with second-order factors including perceived social presence, perceived gratification and perceived social influence. First-order factors are grouped by technical, individual and social factors. Smart PLS 2.0 was used to conduct empirical analysis. The analysis results supported the validity of the research model.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.367-376
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• 2022

In traditional criminal cases, there is a limit to information collection because information on the subject of investigation is provided only with personal information held by the national organization of legal. Surface web-based OSINT(Open Source Intelligence), including SNS and portal sites that can be searched by general search engines, can be used for meaningful profiling for criminal investigations. The Korean-style OSINT workflow can effectively profile based on OSINT, but in the case of individuals, OSINT that can be collected is limited because it begins with "name", and the reliability is limited, such as collecting information of the persons with the same name. In order to overcome these limitations, this paper defines information related to individuals, i.e., equivalent information, and enables efficient and accurate information collection based on this. Therefore, we present an improved workflow that can extract information related to a specific person, ie., equivalent information, from OSINT. For this purpose, different workflows are presented according to the person's profile. Through this, effective profiling of a person (individuals) is possible, thereby increasing reliability in collecting investigation information. According to this study, in the future, by developing a system that can automate the analysis process of information collected using artificial intelligence technology, it can lay the foundation for the use of OSINT in criminal investigations and contribute to diversification of investigation methods.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.