• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.145-154
• /
• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of Korea Society of Industrial Information Systems
• /
• v.19 no.4
• /
• pp.105-117
• /
• 2014

Acquisition of information through the broadcast media is essential for modern life and each broadcaster has progressed its service over the internet with the development of digital technology. Under this circumstance, this study presented the results which compared and analyzed the web accessibility evaluation for Korea, USA, and Japan's leading broadcaster web sites. According to the study results, there was no significant difference in the level of accessibility in all web sites of three countries, but accessibility compliance rate such as alternate text, skip-navigation of repeated region, and title was somewhat insufficient for Korean web sites. In addition, accessibility errors in the brightness contrast of the text contents, the run of the functions that a user doesn't have any intention, the clear statement of the default language, and the label provision were investigated. Therefore, Korean broadcasters should urgently improve and modify these errors and problems for effective web accessibility.

• Korean Journal of Cognitive Science
• /
• v.19 no.3
• /
• pp.223-255
• /
• 2008

In this paper, we introduce an automatic system of scoring English essays. The system is comprised of three main components: a spelling checker, a grammar checker and a lexical cohesion checker. We have used such resources as WordNet, Link Grammar/parser and Roget's thesaurus for these components. The usefulness of an automatic scoring system depends on its reliability. To measure reliability, we compared the results of automatic scoring with those of manual scoring, on the basis of the Kappa statistics and the Multi-facet Rasch Model. The statistical data obtained from the comparison showed that the scoring system is as reliable as professional human graders. This system deals with textual units rather than sentential units and checks not only formal properties of a text but also its contents.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.11b
• /
• pp.853-856
• /
• 2003

바이오 텍스트 마이닝을 위한 정보 추출의 첫 단계는 생물학적 문헌으로부터의 유전자, 단백질, 세포조직 등과 같은 생물학적 개체명의 인식이다. 생물학적 개체명의 명명법상 특징이 매우 다양하고 저자의 개성에 의해 쉽게 좌우되어 단순히 규칙이나 학습 방법 만으로는 쉽게 개체명들을 인식할 수 없다. 또한, 생물학 관련 문헌에 나오는 가능한 모든 개체명과 이들의 모든 변형을 수록하는 것은 현실적으로 불가능하므로 이를 해결하기 위해 이미 알려진 개체명에 대해서 기본적으로 사전을 탐색하고 알려지지 않은 용어들을 규칙과 통계 기반 방법을 통하여 인식하는 것이 효과적이다. 그러나 만족할 만한 수준의 양질의 사전을 구축하는 것은 쉽지 않을 뿐만 아니라 많은 비용이 소요되며, 어느 순간 만족할 만한 성능을 낼 수 있는 사전을 구축했다. 할지라도 유지 관리 하는 것이 결코 쉬운 일이 아니며 마찬가지로 많은 비용을 필요로 하게 된다. 따라서, 잘 구축된 자원으로부터 필요한 정보를 추출하여 적절한 사전을 자동으로 구축하여 활용하는 방법을 사용할 경우, 사전 구축 및 관리에 드는 많은 비용을 줄이면서도 상당히 효과적인 성능을 얻을 수 있을 것이다. 본 연구에서는 바이오 텍스트 마이닝 엔진을 위한 생물학적 개체명 사전을 자동으로 구축하고 이를 쉽게 관리하도록 하는 도구를 개발하였다.

• Korean journal of communication and information
• /
• v.55
• /
• pp.100-118
• /
• 2011

The purpose of this study is to investigate the meaning of cultural practices of videogame audience with 'mod'. Videogame audience members are recognized as very active and interactive beings compared with other interpretive media audience members. Especially mod is one of the most dramatic cultural situation of videogame. It's very prominent properties are 'activity' and 'interactivity'. Videogame audience members, so called 'gamers' modify videogame software as their own sake and use it as their own intention. Modifying and playing with videogame, or 'modding' is very strong cultural program of gamer. Mod is one of avant-garde technology but its practice is not always radical. I observed practices of the members of Naver cafe 'Elderscroll' playing . They used mods of for their phallocentric desire. And they construct a hierarchical and top-dowon membership. So advanced technology and cultural media and text from it does not assure the same advanced contents.

• Journal of KIISE:Computing Practices and Letters
• /
• v.11 no.3
• /
• pp.275-283
• /
• 2005

Ontologies are the core components of the Semantic Web and knowledge-based systems. But it is difficult to find useful ontologies in actual domains. In order to build useful domain ontology, the conceptualization of the domain knowledge by knowledge experts of the specific domain and the specification of conceptualized knowledge with formal languages by ontology designers are required. In addition, structured and detailed guidelines and methods should be provided to be shared by the development team members. However, existing ontology building methodologies define and describe the skeletal structure of the whole building process at the top-layer. We build a useful academic ontology that is based on the conceptual knowledge structure in the domain of philosophy, and propose a detailed methodology to build a text ontology based on Topic Maps. Our methodology consists of two phases, ontology modelling and ontology implementation. We implement a philosophy knowledge portal to support retrieving and navigating of the philosophy knowledge.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.203-217
• /
• 2020

The purpose of this study was to perform a convergence study for investigating main features and influencing factors in career development process, throughout the whole periods of education, that might influence their ultimate choice of majors. We collected data of career development process at the elementary, middle, high school, and college levels using career-o-grams, for the college students who majored in English Lang/Lit and Global Commerce, and we applied text mining techniques for qualitative data analysis. Two major factors influencing career goals were parents and teachers. In particular, teachers were most influential in the career decisions at the middle school level. Teachers, family situations, and peers showed a negative impact on career aspiration. The findings would serve as a guide for career consultants and education program developers.

• The Journal of the Korea Contents Association
• /
• v.19 no.4
• /
• pp.197-206
• /
• 2019

This study aims to analyze through the integrated textbooks whether writing tasks are designed to be successful in cultivating students' writing abilities in the general-purpose Korean language education. First, we established the concept and the components of the writing task based on the definitions mentioned in previous research. The analysis of the types of writing tasks revealed "free writing" and "imitation and writing" to be the most frequent types of writing tasks in both textbooks. The textbooks have only twenty-one subjects in common. And most instructions provide only themes and genres, excluding the purpose, form, quantity, and time necessary for the article or for comprehending the instructions. In these tasks, the reading passages are most often explanatory text. The scoring criteria and time were not provided for the evaluation criteria and other factors. Therefore it became necessary to express the components of the writing task as explicitly and concretely as possible to improve learners' performances.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.2
• /
• pp.79-88
• /
• 2022

Social media big data includes a lot of information that can identify not only consumer consumption patterns but also local images. This paper was collected annually data including 'Samcheok' from 2015 to 2019 from Blog and Cafe of Naver and Daum in domestic portal site, and analyzed the regional image change after refining keyword which forms the regional image by performing text mining and network analysis. According to the research results, the regional image of 2015 was expressed with image cognitive elements of the nearby place name or place etc. such as 'Jangho Port', 'Donghae', and 'Beach'. However the regional image both 2016 and 2019 were changed with image cognitive elements of 'SamcheokSolbich' which is a special place within region. Therefore as the keywords related to the local image include 'Jangho Port' and Resort, which are the representative attractions of Samcheok, it can be seen that the infrastructure factor plays a big role in forming the local image. The significance test for the network data used the bootstrap technique, and the p-values in 2015, 2016, and 2019 were 0.0002, 0.0006, and 0.0002, respectively, which were found to be statistically significant at the significance level of 5%.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.6
• /
• pp.115-126
• /
• 2022

The purpose of this study is to try to IPA(Importance-Performance Analysis) by applying text mining approaches to user review data for korea mobile banking applications, and to derive priorities for improvement. User review data on mobile banking applications of korea commercial banks (Kookmin Bank, Shinhan Bank, Woori Bank, Hana Bank), local banks (Gyeongnam Bank, Busan Bank), and Internet banks (Kakao Bank, K-Bank, Toss) that gained from Google playstore were used. And LDA topic modeling, frequency analysis, and sentiment analysis were used to derive key attributes and measure the importance and satisfaction of each attribute. Result, although 'Authorizing service', 'Improvement of Function', 'Login', 'Speed/Connectivity', 'System/Update' and 'Banking Service' are relatively important attributes when users use mobile banking applications, their satisfaction is not at the average level, indicating that improvement is urgent.