• Journal of the Korea Society of Computer and Information
• /
• v.4 no.4
• /
• pp.47-56
• /
• 1999

We design and implement an ORDBMS-based geographic information system for sightseeing information of Chungbuk to verify the performance and applicability of GEUS/XTM ORDBMS. We Acquire the positional coordinates of the boundaries of administrative districts , roads, and railroads, determine the various kinds of information such as the locations of sightseeing sites, lodgings, and so on, design an object-relational schema using OMT, and implement the geographic information system including a database system. Through the examination of selective accessibility on the sightseeing inform ation database by the various queries, we conclude that the ORDBMS is more applicable than other DBMSs in modeling, storing, referring, and managing of non-fixed complex data such as sightseeing information. Therefore, ORDBMSs provide efficient and extensible implementations of databases and information services from various sources for the increasing demand on geographic information service on internet.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.1
• /
• pp.111-120
• /
• 2020

As an application of big data and artificial intelligence techniques, this study proposes an atypical language-based sentimental opinion poll methodology, unlike conventional opinion poll methodology. An alternative method for the sentimental classification model based on existing statistical analysis was to collect real-time Twitter data related to parliamentary elections and perform empirical analyses on the Polarity and Intensity of public opinion using attribute-based sensitivity analysis. In order to classify the polarity of words used on individual SNS, the polarity of the new Twitter data was estimated using the learned Lasso and Ridge regression models while extracting independent variables that greatly affect the polarity variables. A social network analysis of the relationships of people with friends on SNS suggested a way to identify peer group sensitivity. Based on what voters expressed on social media, political opinion sensitivity analysis was used to predict party approval rating and measure the accuracy of the predictive model polarity analysis, confirming the applicability of the sensitivity analysis methodology in the political field.

• Journal of the Korean Society for information Management
• /
• v.28 no.1
• /
• pp.89-104
• /
• 2011

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In order to extract these entities automatically from scientific documents at once, we developed a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer and terminology extractor.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.1
• /
• pp.31-36
• /
• 2019

A chatbot is an important area of mobile service, which understands informal data of a user as a conversational form and provides a customized service information for user. However, there is still a lack of a service way to fully understand the user's natural language typed query dialogue. Therefore, in this paper, we extract meaningful words, such a region, a food category, and a restaurant name from user's dialogue sentences for recommending a restaurant. and by comparing the extracted words against the contents of the knowledge database that is built from the hashtag for recommending a restaurant in SNS, and provides user target information having statistically much the word-similarity. In order to evaluate the performance of the restaurant recommendation chatbot system implemented in this paper, we measured the accessibility of various user query information by constructing a web-based mobile environment. As a results by comparing a previous similar system, our chabot is reduced by 37.2% and 73.3% with respect to the touch-count and the cutaway-count respectively.

• Journal of health informatics and statistics
• /
• v.43 no.4
• /
• pp.329-335
• /
• 2018

Objectives: In recent years, there has been an increased need for a way to extract desired information from multiple medical literatures at once. This study was conducted to confirm the usefulness of unstructured data analysis using previously published medical literatures to search for new indications. Methods: The new indications were searched through text mining, network analysis, and topic modeling analysis using 5,057 articles of atorvastatin, a treatment for hyperlipidemia, from 1990 to 2017. Results: The extracted keywords was 273. In the frequency of text mining and network analysis, the existing indications of atorvastatin were extracted in top level. The novel indications by Term Frequency-Inverse Document Frequency (TF-IDF) were atrial fibrillation, heart failure, breast cancer, rheumatoid arthritis, combined hyperlipidemia, arrhythmias, multiple sclerosis, non-alcoholic fatty liver disease, contrast-induced acute kidney injury and prostate cancer. Conclusions: Unstructured data analysis for discovering new indications from massive medical literature is expected to be used in drug repositioning industries.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.476-476
• /
• 2017

최근 갑작스런 폭우로 인한 제방 붕괴, 침수 및 지진 등과 같은 재해 발생 시 추가 피해를 방지하고 주민들의 긴급대피를 도운 건 SNS를 통한 현장 정보와 경보 메시지의 지속적인 전파이다. 최근의 SNS는 재난정보에서도 활용할 수 있을 정도로 진화하였다. 국가재난정보 중 수재해 관련 정보를 추출하여 다양한 주제도위에 중첩으로 공간정보를 제공할 수 있는 재난정보 제공을 위한 웹서비스를 개발하고자 하였다. 수재해 정보를 필터링하기 위하여 우선 관련된 키워드 선정이 필요하며, 기본적인 키워드는 하천일람표를 참고하여 6개 권역 및 하천이름을 선정하였다. 또한, 한강 홍수 통제소의 수자원 용어사전과 (사)한국물학술단체연합회에서 발간한 물용어집을 참고하여 수재해 관련 용어들 약 300여개를 추가하였다. 선정된 용어들은 1차적으로 적재된 데이터베이스에서 수재해 정보 관련 필터링을 하는데 사용되며, 비정형 데이터들을 필터링하고 주소 정보 검색 및 추출을 통하여 정형화 하게 된다. 추출된 주소정보에 대하여 개발한 지오코딩 모듈을 적용하여 수재해 항목에 대해 좌표정보를 업데이트 하게 된다. 가뭄, 집중호우, 홍수 등의 수재해 정보별, 또한 일자별 그룹화 및 구조화를 진행하고 해당되는 정보를 공간정보 오픈플랫폼 API를 활용하여 지도상에 가시화할 수 있다. 개발한 지오코딩 모듈을 이용하여 실제 테이블 정보를 구성하여 데이터베이스에 수재해 정보 지오코딩 테이블을 구성하여 테스트 모의하였다. 재난정보 중 홍수, 가뭄에 대한 선택정보와 시간정보를 매개변수로 받는 XML 웹서비스 테스트로 검증을 하였다. 본 연구를 통하여 재난정보 가시화에 있어서 사용자가 조회하고자 하는 유형별, 날짜별 선택이 가능한 공간적 정보를 검색 및 확인할 수 있게 되었다. 개발한 수재해 정보 지오코딩 모듈 프로토 타입은 수재해 정보 플랫폼 융합기술 연구단에서 개발하는 핵심 목표시스템 내 재난정보 제공시스템에 적용 가능하며, 수재해 정보에 대하여 대국민 서비스가 가능할 것으로 사료된다.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.1
• /
• pp.113-117
• /
• 2022

Additive manufacturing (AM, also known as 3D printing) technology is digitalized technology, making it easy to predict and manage quality and also, have design freedom ability. With these advantages, AM technology is applied to various industries. In particular, a method of manufacturing buildings and infrastructure with AM technology is being proposed to the construction industry. However, the application of AM technology is restricted due to problems such as insufficient history and quality of technology, lack of construction management methods, and certification of manufacturing products. Therefore, the manufacture of architectural products is implemented with indirect AM technology. In particular, it manufactures formwork using AM and injecting building materials to implement the architectural product. In this study, hybrid type material extrusion AM is used to manufacture large-sized formwork and implement building products. Moreover, we identify factors that can predict productivity and economic feasibility in the additive manufacturing process. As a result, design optimization results are proposed to reduce the production cost and time of architecture buildings.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.12
• /
• pp.61-67
• /
• 2021

In this paper, we propose a method of extracting and recognizing related information for research from images of the unstructured pulmonary function test papers using character detection and recognition techniques. Also, we develop a post-processing method to reduce the character recognition error rate. The proposed structuring method uses a character detection model for the pulmonary function test paper images to detect all characters in the test paper and passes the detected character image through the character recognition model to obtain a string. The obtained string is reviewed for validity using string matching and structuring is completed. We confirm that our proposed structuring system is a more efficient and stable method than the structuring method through manual work of professionals because our system's error rate is within about 1% and the processing speed per pulmonary function test paper is within 2 seconds.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.6
• /
• pp.119-124
• /
• 2022

Recently a method of constructing architectural products using additive manufacturing technology has been proposed. The additive manufacturing technology automates the construction process and it can secure the safety of workers. In addition, due to the high implementation efficiency of atypical shapes, the applicability to the manufacturing process of buildings and infrastructure is drawing attention. Additive manufacturing technology has the ability of satisfying computer-based construction automation, resource management and construction period prediction which is required in the modern construction industry. However, the industrial application is still limited by insufficient data, standards, regulations, and operating methods. In this study, in order to analyze the applicability of architectural additive manufacturing technology, we manufacture each architectural product with two additive manufacturing systems. In addition, we apply an application of each building product into an appropriate manufacturing system through the AM production decision model. And identify problems in the manufacturing process through empirical experiments. As a result, we propose an extended additive production decision model to improve the quality of building products.

• The Journal of Korean Medical History
• /
• v.35 no.2
• /
• pp.45-67
• /
• 2022

Currently, there are about 20,000 or so known ancient medical texts from the East Asian medical traditions. Although the most famous texts are widely known, many texts still exist only as original manuscripts. We are interested exploring these texts to uncover the potential benefits of their therapeutic knowledge. This study aims to develop a database program that automatically converts the treatment skills described in the text version into a more structured version. In the previous study, our team analyzed patterns in the way that treatment skills are described and then tried to design a database program algorithm that identified every meaningful keyword used to describe treatment skills and put that word in the right cell of a structured table. This study continues the development of this program. East Asian medical herbal treatment information is broken down into 4 elements: the first one is the name or title of treatment skills, and the second is the symptoms to which the treatment is applied, the third is ingredients used, the fourth is how information is processed and the indications taken. This study presents the algorithm's principles on how to analyze and structure the fourth element, the processing of information and taking of indications, which is described in a form of ancient natural language.