Keyword-based networked knowledge map expressing content relevance between knowledge

Yoo, Keedong(유기동) 한국지능정보시스템학회 2018 지능정보연구 Vol.24 No.3

A knowledge map as the taxonomy used in a knowledge repository should be structured to support and supplement knowledge activities of users who sequentially inquire and select knowledge for problem solving. The conventional knowledge map with a hierarchical structure has the advantage of systematically sorting out types and status of the knowledge to be managed, however it is not only irrelevant to knowledge user’s process of cognition and utilization, but also incapable of supporting user`s activity of querying and extracting knowledge. This study suggests a methodology for constructing a networked knowledge map that can support and reinforce the referential navigation, searching and selecting related and chained knowledge in term of contents, between knowledge. Regarding a keyword as the semantic information between knowledge, this research’s networked knowledge map can be constructed by aggregating each set of knowledge links in an automated manner. Since a keyword has the meaning of representing contents of a document, documents with common keywords have a similarity in content, and therefore the keyword-based document networks plays the role of a map expressing interactions between related knowledge. In order to examine the feasibility of the proposed methodology, 50 research papers were randomly selected, and an exemplified networked knowledge map between them with content relevance was implemented using common keywords.

The Impact of L1 Reading Skill and L2 Knowledge on L2 Reading Skill of Korean College EFL Learners

김우영 한국영어학회 2006 영어학 Vol.6 No.2

Kim, Woo-Young. 2006. The Impact of L1 Reading Skill and L2 Knowledge on L2 Reading Skill of Korean College EFL Learners. Korean Journal of English Language and Linguistics. 6-2, 235-254. Not a few might assume that L2 reading skill is not related to L1 reading skill and semantic knowledge is the more important component in L2 reading. The purpose of the present study is to investigate the interrelations between the L1 and L2 reading abilities and L2 syntactic knowledge and L2 semantic knowledge, and L2 reading ability with the subjects of Korean college EFL learners. Tests for measuring reading comprehension of L1 and L2 and linguistic ability including semantic and syntactic knowledge of L2 were administered with separate test sets on different days. The results were analyzed with analysis method of correlation between L1 and L2 reading skill, and with regression between L2 reading skill and other linguistic components of L2. The findings suggest: firstly L2 reading skill is transferred from L1 reading skill, secondly, both L1 semantic and syntactic knowledge are integral components of second language reading comprehension, but syntactic knowledge can influence more on learners' L2 reading skill. Thus, it is imperative that the role of syntactic knowledge as well as semantic knowledge in L2 reading must not be neglected according to the learners' level.

웹 자료 수집을 활용한 언어 지식그래프 개발 - 정서 장애 주제 분야의 사례 연구 -

조은경,강승식 한국어의미학회 2020 한국어 의미학 Vol.67 No.-

This paper aims to show how to develop a knowledge graph as linguistic knowledge-base for linguistic artificial intelligence applications. Firstly, we investigate the previous researches and developments of knowledge graphs which have been developed so far and are the extensions of lexicon and ontology which are well-known forms of linguistic knowledge bases. Secondly, we describe how to develop a knowledge graph in the domain of affective disorder as a case study based on expert knowledge data and general text data. In the process of doing this, we would like to show how to collect language resources from the Web which have popular influences on people and try to make formalisation of representation way of linguistic knowledge in the domain of psychology. Finally, we show the application of using a knowledge graph as a semantic knowledge-base. Overall, we would say that a linguistic knowledge graph still would be one of the knowledge powers which will be linguistically explainable by humans in the world of digital data analysis floods.

Economics Knowledge Sharing Method using Semantic Web Technologies

Donghee Yoo(유동희),Sungchun No(노성천) 한국지능정보시스템학회 2013 한국지능정보시스템학회 학술대회논문집 Vol.2013 No.6

The objective of this paper is to argue the need for economics knowledge sharing as well as demonstrate that it can be effectively achieved by using Semantic Web technologies. To this end, we first designed an economics knowledge sharing ontology (EKSO) to describe economic domain knowledge. We then implemented an ontologybased economics knowledge sharing system (OEKSS) based on the EKSO and various Semantic Web technologies in order to demonstrate how we can use shared economics knowledge for future economics research.

웹기반 협업설계과정에서 공조방식 설계지식을 지원하기 위한 지식베이스 시스템의 모델개발에 관한 연구

우세진 대한건축학회 2007 대한건축학회논문집 Vol.23 No.2

Recently, the architectural working surroundings are being changed rapidly and greatly. As the result of that, it is required that the architectural specialists adjust and connect them mutually regardless of time and space. Web-based Integrated Architectural Design Assistant Program (Cyber-Architect) has been developed as a method to deal with such variable working surroundings. It is very important step to develop the knowledge-based system that controls the knowledges which are caused and inputted in the inference process, with interlocking the inference engine of the Design Assistant Program. Accordingly, the additional surveys and interviews have been carried out, on the basis of the results from the precedent studies and interviews on HVAC type decision process, in order to set up the prototype model to develop the knowledge-based system of Design Assistant Program. The relation between architectural design and HVAC type decision process has been set up in this study. The type and the characteristic of the related design knowledges, and the position and the role of the knowledge-based system in the process of decision, have been analyzed by setting up the mutual relationship. As the results, the prototype model of knowledge-based system has been able to be offered through the semantic object model.

의미범주 지식의 다양성과 보편성

정유진(Chung, Eugene),황유미(Hwang, Yu Mi),홍정하(Hong, Jungha) 담화·인지언어학회 2014 담화와 인지 Vol.21 No.3

This study discusses semantic knowledge and subcategorization of animals for Koreans based on a semantic verbal fluency task. Compared to many previous studies which focused on the number of animals in response or the switches between clusters, we aim to identify diversity and universality of semantic knowledge about animals and to propose subcategories of animals. Instead of using pre-existing semantic categories proposed by previous studies, we argue for Korean specific semantic knowledge and categories of animals based on healthy Korean adults’ semantic knowledge. We evaluated 275 cognitively healthy volunteers, aged 45 to 86 years. An educational average level ± standard deviation for the whole sample is 9.89 ± 4.2 years. As a result of the fluency task, the participants mentioned 193 different types of animals with the number of 4,047. They named an animal with the following order of preferences: ‘a tiger, a dog, a cow, a pig, a chicken, a lion, an elephant, a horse, a duck, a rabbit, a giraffe, etc.’ The top ranked animals among 193 types in naming can be regarded as a “typical” animal among Korean people. With respect to category-based induction, typicality can be a case of a more universal tendency. In order to examine subcategories of animals, we extracted a bigram from the response list. We derived dice distances to measure similarity between two co-occurring items and provided a perceptual map based on multidimensional scaling with statistical methods using R.

의미 기반의 지식모델 통합과 탐색에 관한 연구

전승수 ( Seung-su Chun ) 한국인터넷정보학회 2014 인터넷정보학회논문지 Vol.15 No.6

최근 자연어 및 정형언어 처리, 인공지능 알고리즘 등을 활용한 효율적인 의미 기반 지식모델의 생성과 분석 방법이 제시되고 있다. 이러한 의미 기반 지식모델은 효율적 의사결정트리(Decision Making Tree)와 특정 상황에 대한 체계적인 문제해결(Problem Solving) 경로 분석에 활용된다. 특히 다양한 복잡계 및 사회 연계망 분석에 있어 정적 지표 생성과 회귀 분석, 행위적 모델을 통한 추이분석, 거시예측을 지원하는 모의실험 모형의 기반이 된다. 하지만 대부분의 지식 모델은 특정 지표나 정제된 데이터를 수동적으로 모델링하여 분석에 활용한다. 본 논문에서는 텍스트 마이닝 기술을 통해 방대한 비정형 정보로부터 지식 모델을 구성하는 토픽 인자와 관계 노드를 생성하고 이를 통합하는 방법과 정형적 알고리즘을 제시한다. 이를 위해 먼저, 텍스트 마이닝을 통해 도출되는 키워드 맵을 동치적 지식맵으로 변환하고 이를 의미적 지식모델로 통합하는 방법을 설명한다. 또한 키워드 맵으로부터 유의미한 토픽 맵을 투영하는 방법과 의미적 동치 모델을 유도하는 알고리즘을 제안한다. Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available,

차세대 지식관리시스템 아키텍쳐에 관한 연구

전종홍 명지대학교 금융지식연구소 2004 금융지식연구 Vol.2 No.2

There have been various attempts of Knowledge Management System in order to effectively support Knowledge Process and to manage a wide variety of unstructured knowledge. However, Knowledge Management System basically has some significant weakness for searching knowledge, extracting information and maintenance, and some difficulties to integrate such various knowledge resources. Several studies had been conducted to overcome these weaknesses and to improve the method of knowledge management. The purpose of this study is 1) to examine the effectiveness of Next Generation Web Technology that has a great attention lately; whether it is useful to overcome the weaknesses, and 2) to review its strong points and some future uses. Further, differences of Next Generation Web Technology compared to existing Knowledge Management System Architecture are reviewed. Finally, a new Semantic Web Enabled KMS Architecture is proposed. Also some prospects for future market direction are suggested. 오늘날 지식관리시스템은 효과적으로 지식 프로세스를 지원하고 다양한 비정형의 지식들을 처리하기 위한 다양한 시도들을 하고 있다. 그러나 지식 검색, 정보 추출, 관리 등에서 근본적인 약점을 갖고 있으며, 다양한 지식 자원들을 통합하고 연동하는데 어려움을 갖고 있다. 이런 한계들을 극복하고 지식관리 방식을 개선하기 위한 다양한 연구들이 시도되고 있다. 본 논문에서는 최근 주목받고 있는 차세대 웹 기술을 적용함으로써 지식관리시스템들이 직면한 한계들을 극복할 수 있는지, 그리고 어떤 장점과 기회들을 얻을 수 있는지 고찰하였다. 그리고 기존 지식관리시스템 아키텍처와 비교하여 변경되는 부분들을 살폈으며, 새로운 차세대 지식관리시스템 아키텍처와 향후 전망, 그리고 나아갈 바를 제시하고자 하였다.

Semantic Web Services on the Business Support

Jin Sung Kim(김진성),Soon Jae Kwon(권순재) 한국지능정보시스템학회 2010 한국지능정보시스템학회 학술대회논문집 Vol.2010 No.11월

During the decades, considerable human interventions to comprehend the web information were increased continually. The successful expansion of the web services made it more complex and required more contributions of the users. Many researchers have tried to improve the comprehension ability of computers in supporting an intelligent web service. One reasonable approach is enriching the information with machine understandable semantics. They applied ontology design, intelligent reasoning and other logical representation schemes to design an infrastructure of the semantic web. For the features, the semantic web is considered as an intelligent access to understanding, transforming, storing, retrieving, and processing the information gathered from heterogeneous, distributed web resources. The purpose of this study is to investigate the research trends on semantic web applications.

Semantic-based Mashup Platform for Contents Convergence

Yongju Lee,Hongzhou Duan,Yuxiang Sun The Institute of Internet 2023 International journal of advanced smart convergenc Vol.12 No.2

A growing number of large scale knowledge graphs raises several issues how knowledge graph data can be organized, discovered, and integrated efficiently. We present a novel semantic-based mashup platform for contents convergence which consists of acquisition, RDF storage, ontology learning, and mashup subsystems. This platform servers a basis for developing other more sophisticated applications required in the area of knowledge big data. Moreover, this paper proposes an entity matching method using graph convolutional network techniques as a preliminary work for automatic classification and discovery on knowledge big data. Using real DBP15K and SRPRS datasets, the performance of our method is compared with some existing entity matching methods. The experimental results show that the proposed method outperforms existing methods due to its ability to increase accuracy and reduce training time.