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      • KCI등재

        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.

      • KCI등재

        Mobile Device and Virtual Storage-Based Approach to Automatically and Pervasively Acquire Knowledge in Dialogues

        Keedong Yoo(유기동) 한국지능정보시스템학회 2012 지능정보연구 Vol.18 No.2

        The Smartphone, one of essential mobile devices widely used recently, can be very effectively applied to capture knowledge on the spot by jointly applying the pervasive functionality of cloud computing. The process of knowledge capturing can be also effectively automated if the topic of knowledge is automatically identified. Therefore, this paper suggests an interdisciplinary approach to automatically acquire knowledge on the spot by combining technologies of text mining-based topic identification and cloud computing-based Smartphone. The Smartphone is used not only as the recorder to record knowledge possessor’s dialogue which plays the role of the knowledge source, but also as the sensor to collect knowledge possessor’s context data which characterize specific situations surrounding him or her. The support vector machine, one of well-known outperforming text mining algorithms, is applied to extract the topic of knowledge. By relating the topic and context data, a business rule can be formulated, and by aggregating the rule, the topic, context data, and the dictated dialogue, a set of knowledge is automatically acquired.

      • KCI등재후보
      • KCI등재

        연관지식의 효율적인 표현 및 추론이 가능한 지식그래프 기반 지식지도

        유기동(Yoo, Keedong) 한국지능정보시스템학회 2021 지능정보연구 Vol.27 No.4

        Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous researchs data to check whether this study’s knowledge map can yield the same level of performance as the previous one did. Previous research’s case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research’s validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research’s ontology-based approach, this studys Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This studys artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting users cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of

      • KCI우수등재

        비휘발적 소셜 큐레이션 서비스가 가능한 대화형 상거래 플랫폼 개발

        유기동(Keedong Yoo) 한국전자거래학회 2018 한국전자거래학회지 Vol.23 No.3

        동일한 관심사를 갖는 개인 또는 그룹에서 생성 및 공유한 정보를 선별하여 제공하는 소셜큐레이션 서비스는, 최근 많이 사용되고 있는 SNS 기반 채팅 기능과 접목될 경우 시너지적 효과를 기대할 수 있다. 특히 이러한 기술이 제품 및 서비스를 판매하는 인터넷 쇼핑몰에 적용될 경우, 구매자는 채팅을 통해 보다 신뢰할 수 있는 정보를 실시간으로 제공받을 수 있으며, 판매자는 자사 제품 및 서비스에 관심을 갖는 고객에게 차별적이고 풍부한 정보를 지속적으로 제공할 수 있다. 본 연구는 소셜 큐레이션 서비스를 채팅 기반으로 제공하는 대화형 상거래 플랫폼을 제시한다. 제시된 상거래 플랫폼은 상점 및 상품별로 채팅 채널을 구성하여 상점 및 브랜드, 그리고 세부 상품에 대한 신규 및 기존 고객의 문의에 실시간으로 대응할 수 있고, 해당 채널에 가입된 고객에게 차별화된 판매전략을 지속적으로 구사할 수 있도록 구성되었다. 특히 MongoDB를 이용하여 채널별 수록된 정보와 채팅 내역이 반영구적으로 저장 및 보관되도록 하여, 구매자가 언제든 해당 채널에 수록된 제품 정보와 채팅 내역을 검색 및 참고할 수 있도록 구성하였다. The social curation service that selectively provides information generated by individuals or groups with the same interests can have a synergistic effect when combined with the recently used SNS-based chatting function. If these kinds of chatting-based curation technologies are applied to the Internet shopping malls, particularly, buyers can obtain more reliable information in real time basis, and sellers can provide them with more differentiated and rich information in a continuous manner. This research suggests a chatting-based commerce platform that provides the social curation service based on chats among sellers, existing buyers, and potential buyers. The proposed commerce platform can organize a chat channel for each store and product not only to immediately respond to new and existing customer inquiries about stores, brands, and detailed products, but also to continuously activate differentiated sales strategies to customers subscribed to the channel. In particular, MongoDB is used to permanently save and archive the information and chatting history of each channel, so that the buyer can search and refer to them recorded in the corresponding channel at any time.

      • KCI등재

        온톨로지를 이용한 프로세스 기반 지식지도 구축

        유기동(Keedong Yoo),황현석(Hyunseok Hwang) 한국산업정보학회 2012 한국산업정보학회논문지 Vol.17 No.4

        지식지도는 지식 간의 상호 연관성을 기초로 전체적인 지식의 현황을 보여주는 도식으로, 상황에 따라 다양하게 해석 및 적용될 수 있는 지식의 특성을 보다 형식화되고 정형화된 방식으로 표현하기 위해 온톨로지 기술의 적용이 필요하다. 본 연구는 지식 네트워크에 나타나는 지식 간 상호참조적 네비게이션이 가능하도록 온톨로지 기술을 기반으로 지식지도를 정의하고 표현하는 방법론을 제시한다. 제시된 방법론의 타당성을 검증하기 위하여, 온톨로지 모델링 도구인 Protege-OWL을 이용하여 실제 지식지도를 모델링하고, 몇 가지 예제를 통해 구현된 온톨로지 기반 지식지도가 실제로 지식 간의 상호참조적 네비게이션을 반영하는 지식 네트워크를 구성하는지 알아본다. A knowledge map is a diagramed network among knowledge which is related with each other in terms of the referential navigation. To formally as well as structurely represent various contextual use of knowledge, the ontology technology has been recommended to be applied. This research proposes a methodology to build the ontology-based knowledge map promoting referential navigation between knowledge. To prove the validity of the proposed concepts, an ontology-based knowledge map is designed as an example, which demonstrates whether the designed knowledge network in the knowledge map is underpinned by the referential navigation between knowledge.

      • KCI우수등재

        음성형 지식의 자율적 관리 및 서비스를 위한 애플리케이션 스위트 개발

        유기동(Keedong Yoo) 한국전자거래학회 2016 한국전자거래학회지 Vol.21 No.1

        문제 상황에 처한 사용자가 정보기술 역량을 활용하여 언제 어디서든 문제의 해결에 필요한 정보 및 지식을 완전히 자동화된 방식으로 제공받을 수 있도록 하는 자율적 지식서비스는, 사용자의 지적 탐구욕구의 증가와 더불어 정보기술 인프라의 고도화에 따라 더욱 많은 관심을 받고 있다. 기존의 지식서비스는, 지식의 획득과 분배 과정을 모두 다루는 것이 아닌, 지식의 분배 과정에 편향되어 집중되는 문제점을 갖고 있어, 사용자에게 분배되는 지식의 품질요건에 입각한 지식의 획득이 이루어지지 못한다. 따라서 본 연구는 지식이 획득되는 단계부터 사용자에게 분배되는 단계까지 일련의 과정을 완전 자동화하는 자율적 지식서비스의 프레임워크를 제시한다. 또한 이를 구성하는 요소기술을 도출 및 명세하여, 자율적 지식서비스의 프로토타입 시스템인 ASKs(Application Suite for Knowledge Service)를 개발한다. 본 연구를 통해, 특정기술에 국한되어 정의되는 지식서비스의 범위를 확장하여, 보다 사용자 친화적이며 현실적 적용가능성이 높은 지식서비스의 구현이 촉진될 수 있다. Autonomous knowledge service, a fully-automated and pervasive service for knowledge acquisition and support based on the power of recent ITs is gaining tremendous interest more and more, as not only the level of users’ intelligence increases but also the maturity of IT infrastructure improves. Conventional approaches of knowledge service, however, could not satisfy users because they usually provided undesired knowledge which had been acquired without considering users’ want. In other words, knowledge acquisition and distribution were separately performed. This research, therefore, suggests an amended autonomous knowledge service framework by fully-automating the whole phases of knowledge life cycle, from knowledge acquisition to distribution. ASKs, the prototype system of this research, is also implemented by defining and specifying component technologies which constituently compose suggested framework. More user-friendly and applicable way of knowledge service will be derived and facilitated through this research.

      • KCI등재

        문서 자동요약 기술을 적용한 클라우드 스토리지 기반 지능적 아카이빙 시스템

        유기동(Keedong Yoo) 한국산업정보학회 2012 한국산업정보학회논문지 Vol.17 No.3

        제로 클라이언트 체제는 기업의 문서 중앙화를 위해 제시된 최신의 방법이며, 이를 기업의 현실에 보다 적합하도록 토착화시키는 작업은 필수적이다. 본 연구는 제로 클라이언트 체제의 잘 알려진 보안 및 프라이버시 상의 문제점을 제외한, 사용 상의 문제점을 보완하고자 고안되었다. 즉, 작업자가 작업한 문서를 기업 클라우드 스토리지에 저장하고자 저장 카테고리를 검색하는 과정의 부담과 정확성을 향상시키기 위하여, 작업 문서의 주제어를 자동으로 파악하고, 이를 바탕으로 해당 문서가 저장되어야 하는 카테고리를 자동으로 검색하여 작업자의 확인을 통 해 자동 저장되도록 하는, 지능적 아카이빙 방식을 제시한다. 본 연구에서 제시하는 주제어 자동 파악 및 자동 아카이빙을 위한 방법론과 프로토타입 시스템은 기업 환경에 적용이 가능할 정도로 정확성과 확장성을 갖추고 있다. Zero client-based cloud storage technology is gaining much interest as a tool to centralized management of organizational documents nowadays. Besides the well-known cloud storage’s defects such as security and privacy protection, users of the zero client-based cloud storage point out the difficulty in browsing and selecting the storage category because of its diversity and complexity. To resolve this problem, this study proposes a method of intelligent document archiving by applying an algorithm-based automatic topic identification technology. Without user’s direct definition of category to store the working document, the proposed methodology and prototype enable the working documents to be automatically archived into the predefined categories according to the extracted topic. Based on the proposed ideas, more effective and efficient centralized management of electronic documents can be achieved.

      • KCI우수등재

        지식 간 내용적 연관성 파악 기법의 지식 서비스 관리 접목을 위한 정량적/정성적 고려사항 검토

        유기동(Keedong Yoo) 한국전자거래학회 2021 한국전자거래학회지 Vol.26 No.3

        내용적 연관성에 기반한 연관지식의 파악은 핵심 지식에 대한 서비스와 보안의 기본적인 기능이다. 본 연구는 내용적 연관성을 기준으로 연관지식을 파악하는 기존의 방식, 즉 키워드 기반 방식과 워드임베딩 방식의 연관문서 네트워크 구성 성능을 비교하여 어떤 방식이 정량적/정성적 측면에서 우월한 성능을 나타내는가를 검토한다. 검토 결과 키워드 기반 방식은 핵심 문서 파악 능력과 시맨틱 정보 표현 능력 면에서 우월한 성능을, 워드임베딩 방식은 F1-Score와 Accuracy, 연관성 강도 표현 능력, 대량 문서 처리 능력 면에서 우월한 성능을 나타냈다. 본 연구의 결과는 기업과 사용자의 요구를 반영하여 보다 현실적인 연관지식 서비스 관리에 활용될 수 있다. Identification of associated knowledge based on content relevance is a fundamental functionality in managing service and security of core knowledge. This study compares the performance of methods to identify associated knowledge based on content relevance, i.e., the associated document network composition performance of keyword-based and word-embedding approach, to examine which method exhibits superior performance in terms of quantitative and qualitative perspectives. As a result, the keyword-based approach showed superior performance in core document identification and semantic information representation, while the word embedding approach showed superior performance in F1-Score and Accuracy, association intensity representation, and large-volume document processing. This study can be utilized for more realistic associated knowledge service management, reflecting the needs of companies and users.

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