• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.477-482
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• 2021

The integrated underground space map system provides information on infrastructure that requires security, but to prevent rupture accidents during excavation work at the underground construction site, it must provide information on all underground facilities on the site. Providing additional information other than the object of interest to the user is a factor that increases the risk of information leakage of security data. In this paper, we design the visualization filtering method that when visualizing the integrated underground space map in the field, the visualization of entire underground facilities of interest to workers is performed, but visualization of other underground facilities is minimized to minimize the risk of security data information leakage. To this end, a visualization area of a certain distance for each of the underground facilities of interest was created, and an integrated visualization filter was created with spatial union operation. When the integrated underground map is output on the screen, only the objects located within the filter area are visualized using the generated filter information, and objects that exist outside are not visualized, thereby minimizing the provision of information to the user.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.5
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• pp.323-329
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• 2024

In an era of low interest rates around the world, interest in real estate has increased. We can collect real estate information using the Internet, but it takes a lot of time to find. In this paper, real estate information from January 2015 to April 2024 is collected from three places to help users more easily collect real estate information of interest and use it for sales. First, by analyzing HTML documents using web scraping techniques, information on real estate of interest is automatically extracted from the website of the platform company. Second, the actual transaction price of the real estate is additionally collected through the open API provided by the Ministry of Land, Infrastructure and Transport. Third, real estate-related news is provided so that users can learn about the future value and prospects of real estate. The simulation results for the data collected in this study show that the lowest price predicted by the ARIMA model is expected to be in May 2024 among the next eight months. Therefore, by following this procedure, real estate buyers can make more efficient home sales by referring to related information including the predicted transaction price.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.3
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• pp.109-122
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• 2020

In recent, projection mapping, which has attracted high attention in the field of realistic media, is regarded as a technology to increase the users' immersion. However, most existing methods perform projection mapping on static objects. In this paper, we developed a technology to track the movements of users and dynamically map the media contents to the users' bodies. The projected media content is built by predefined gestures just using the user's bare hands without the special devices. An interactive immersive media system has been implemented by integrating these dynamic projection mapping technologies and gesture-based drawing technologies. The proposed realistic media system recognizes the movements and open / closed states of the user 's hands, selects the functions necessary to draw a picture. The users can freely draw the picture by changing the color of the brush using the colors of any real objects. In addition, the user's drawing is dynamically projected on the user's body, allowing the user to design and wear his t-shirt in real-time.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.346-350
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• 2009

According to the development of information technology, there are many services in our life. These services make our life safe and convenient. However, the increment of the services also causes the increment of human concern and effort to control these services. The context-aware service is the service that provided their functionality at the right time and to the right place by analysis user's current situation. The most previous studies about context-aware service regard that context-aware services are defined by the developer who has expertise in information technology. The definition of the context-aware services by the developer makes difficult to reflect user's personal preferences and life pattern to the services. In this paper, we propose an user interface EUCAS(by End-User, Context-Aware Service development) that make the user can define and manage their own context-aware service according to their preferences. We expect EUCAS can be effective user interface technology for providing personalized context-aware service.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.186-186
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• 2010

최근 들어, 2차원/3차원의 랩 또는 항공/위성 영상의 공간정보를 웹 상에서 서비스 하고 이러한 공간정보에 다양한 정보들을 융 복합하여 사용자들에게 보다 높은 수준의 정보를 제공하기 위한 기술개발에 대한 관심이 급증하고 있다. 예를들어, Microsoft사의 경우는 사용자 참여형(Participatory) 센서 웹 환경을 구축하기 위하여 SenseWeb 관련 기술 개발 및 시범 프로젝트를 수행하고 있는데, SenseWeb 시스템에서는 전 세계에 존재하는 모든 센서들을 연계하여 웹 상에서 사용자들에게 제공할 수 있도록 하는 것을 목표로 하고 있다. 최근에는, 이러한 SenseWeb 시스템을 이용하여 센싱정보와 Bing Map의 공간정보를 융합하여 사용자에게 서비스를 제공할 수 있는 SensorMap 시스템이 개발되었는데, 이러한 SensorWeb/SensorMap 시스템을 기반으로 다양한 시범 프로젝트들이 진행되어 오고 있다. Google사의 경우는 기존에 서비스 되고 Google Eearth/Map을 기반으로 실시간 센싱정보를 연계하여 제공하는 서비스와 다양한 사용자들의 정보들을 테이블 형태로 연계 및 융합하여 제공하기 위한 Google Fusion Tables 서비스를 제공하고 있다. Oracle사의 경우는 센싱정보를 포함하여 실시간으로 끊임없이 변화하는 정보들에 대하여 이벤트 처리, 패턴 분석, 그리고 상황인식 등의 서비스를 제공할 수 있는 CEP(Complex Event Processing) 제품을 선보이고 있다. Nokia사의 경우는 기존의 고정 센서노드들 이외에 모든 모바일 폰을 이동이 가능한 센서노드로 가정하고 이러한 모바일 센서노드들로부터 교통정보를 포함하는 다양한 센싱정보를 수집하고 분석하여 공간정보 기반으로 서비스하기 위한 기술 개발을 꾸준히 추진해 오고 있다. 본 발표에서는 이러한 공간정보와 센싱정보 또는 기타 사용자 정보와의 융 복합서비스를 가능하게 하는 핵심기술들에 대하여 소개하고자 한다. 첫째로 다양한 공간정보와 센싱정보의 융 복합 및 분석 서비스를 제공할 수 있는 u-GIS 융합 엔진에 대하여 설명하고자 한다. u-GIS 융합 엔진에서는 구체적으로 최근 이슈가 되고 있는 다양한 센싱정보의 효율적 수집, 분석, 관리를 위한 GeoSensor 데이터 저장/관리 기술과 센싱정보-공간정보의 실시간 융합 분석 기술에 대해서 소개를 하고자 한다. 둘째로, 이러한 공간정보, 센싱정보 그리고 기타 사용자 정보들을 웹 상에서 효율적으로 매쉬업하여 2차원 및 3차원으로 사용자에게 제공하기 위한 맞춤형 국토정보 제공 기술에 대하여 설명하고자 한다. 여기서는 공간정보 센싱정보 그리고 기타 사용자 정보와의 연계를 위한 매쉬업 엔진 기술 그리고 실시간 3차원 공간정보 제공 기술 등에 대하여 소개를 하고자 한다. 끝으로, 영상 기반의 효율적인 공간정보 구축을 위한 멀티센서 데이터 처리 기술에 대하여 간략히 소개를 하고, 앞에서 설명된 핵심기술들 이외에도 향후 추가로 요구되는 기술개발 내용에 대하여 간략히 설명을 하고자 한다.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.910-919
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• 2012

We have observed huge success in social network services like Facebook and Twitter, and many researchers have done their analysis on these services. As massive data observed by users is produced on Twitter, many researchers have been conducting research to detect an event on Twitter. Some of them developed a system to detect the earthquakes or to find the local festivals. However, they did not consider the credibility of location information on Twitter although their systems were using the location information. In this paper, we analyze the credibility of the profile location and the correlation between the spatial attributes on Twitter as the preliminary research of the event detection system on Twitter. We analyzed 0.5 million Twitter users in Korea and 2.8 million users around the world. 49.73% of the users in Korea and 90.64% of the users in the world posted tweets in their profile locations. This paper will be helpful to understand the credibility of the spatial attributes on Twitter when the researchers develop an application using them.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.457-466
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• 2004

Recommendation is to offer information which fits user's interests and tastes to provide better services and to reduce information overload. It recently draws attention upon Internet users and information providers. The collaborative filtering is one of the widely used methods for recommendation. It recommends an item to a user based on the reference users' preferences for the target item or the target user's preferences for the reference items. In this paper, we propose a neural network based collaborative filtering method. Our method builds a model by learning correlation between users or items using a multi-layer perceptron. We also investigate integration of diverse information to solve the sparsity problem and selecting the reference users or items based on similarity to improve performance. We finally demonstrate that our method outperforms the existing methods through experiments using the EachMovie data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2149-2154
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• 2016

Modern society is deepening people's interest in healthy life. Therefore, the development of research and service related to health is proceeding. In the IT field, healthcare systems using information in the medical field are being developed. Most systems utilize PC and smart TV or use smart phones to provide users with information and movement-related information in the healthcare field. However, algorithms and systems that accurately analyze user 's body information are in development stage. To solve this problem, this paper proposes a system that provides information to the user by analyzing the BMI (Body Mass Index) index and BMR (Basal Metabolic Rate) of the user. The information provided to the user suggests appropriate exercise intensity, appropriate level of exercise, and fitness equipment that are appropriate for the user's body, unlike conventional fitness systems that detect motion and show the calories consumed. In addition, the user can perform efficient exercise based on the recommended information.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.337-342
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user's context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.