온톨로지와 토픽모델링 기반 다차원 연계 지식맵 서비스 연구

정한조(Hanjo Jeong) 한국지능정보시스템학회 2015 지능정보연구 Vol.21 No.4

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations’ data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers’ network is created, and the researchers’ network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the const

A Graph-based Algorithm to Build Knowledge Map for Minority Languages

Lirong Qiu 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.2

Knowledge mapping will undoubtedly bring great convenience to application users for being behind the strong support of knowledge base. In this paper, we study how to discover the evolution of knowledge map in multi-languages. Our approach is uniquely designed to capture the rich topology of semantic items and to link the sub-graph to a global knowledge map. Instead of building a knowledge map start from scratch, we conceptually define semantic classes as a quantized unit of evolutionary link in sub-graph and discover new knowledge with multi-language dictionaries. Discovered new knowledge items are then connected to form an evolution knowledge map using a measure derived from the underlying semantic classes. We integrate these noisy items and entities into a unified probabilistic knowledge map using ideas from graph-based algorithm.

지식 간의 상호참조적 네비게이션이 가능한 프로세스 기반 반자동화 지식지도

유기동 ( Kee Dong Yoo ) 한국지식경영학회 2012 지식경영연구 Vol.13 No.1

A knowledge map is a network-typed diagram visualizing all kinds of knowledge that influences each other to solve a problem. A knowledge map determines the structure of knowledge categorizing and archiving by defining the relationship of referential navigation among knowledge. Since tremendous and increasing number of knowledge needs to be included in a knowledge map, a knowledge map must be organized automatically by considering the contents and relationships of knowledge. This paper suggests the concept and prototype of a semi-automated knowledge map which automatically maps new piece of knowledge onto a manually provided draft map. The prototype knowledge map is based on the recursive programming to make a knowledge map automatically determine the location of the newly-entered knowledge by considering the referential relationship between knowledge. The proposed knowledge enables the knowledge network to expand autonomously by automatically including and storing knowledge. Also, it can improve the accuracy and applicability of knowledge for problem-solving, because the relationship of referential navigation among knowledge can be efficiently and effectively expressed.

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

키워드 기반 문서 네트워크를 이용한 네트워크형 지식지도 자동 구성

유기동 ( Yoo Keedong ) 한국지식경영학회 2018 지식경영연구 Vol.19 No.3

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user’s activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user’s cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user’s activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

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.

Dynamic knowledge mapping guided by data mining: Application on Healthcare

Brahami, Menaouer,Atmani, Baghdad,Matta, Nada Korea Information Processing Society 2013 Journal of information processing systems Vol.9 No.1

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

과학기술 지식맵의 형태적 분류와 정보분석 관점의 지식맵 사례 도출

이방래(Bangrae Lee),이준영(June Young Lee),김도현(Dohyun Kim),노경란(Kyung Ran Noh),양명석(Myung Seok Yang),권오진(Oh-Jin Kwon),최광남(Kwang-Nam Choi),김한준(Han-Joon Kim) 한국콘텐츠학회 2013 한국콘텐츠학회논문지 Vol.13 No.11

본 연구에서는 기존 지식맵을 형태적으로 분류하고 추가적으로 개발되어야 할 지식맵의 유형을 제시함과 동시에 정보분석 관점에서 활용할 만 한 가치가 있는 과학기술 지식맵 모델을 도출하였다. 기존 연구에서 나타난 지식맵의 정의들을 살펴보고 본 연구에서의 정의와 범위를 다시 정리하였다. 또한 육하원칙을 정보속성으로 취하고 이를 기반으로 주요 과학기술 지식맵을 그 형태에 따라서 단순 도표, 트렌드 지식맵, 분포도 지식맵, 네트워크 지식맵으로 분류하였다. 네 가지 과학기술 지식맵 유형에 따라 주요 지식맵의 세부 모델을 정리하고 추가적으로 개발이 필요한 지식맵 모델의 유형도 제시하였다. 마지막으로 정보분석 관점에서 유용한 13가지 지식맵 모델 사례를 도출하고 각 세부 모델에 대한 지식맵의 유형, 정보 항목, 모델의 설명 및 활용 목적 등을 제시하였다. Knowledge maps for science and technology are used extensively in the research projects. However, they are not organized systematically and are not necessarily suitable to be used in the research projects. Therefore, this study aims to organize the knowledge maps in order to support scientific research projects. To this end, the existing knowledge maps for science and technology are classified as one of four types based on data representation methods; the frequency summary map, trend summary map, distribution-based knowledge map and network-based knowledge map. Additionally, by summarizing and classifying the knowledge maps through the principle of five ws and one h, the unexplored area are investigated. Finally, some examples of useful knowledge maps in terms of data analysis are provided with details such as definitions, components and utilization purposes. These findings may be a starting point for future research into a better understanding of knowledge maps for science and technology.

해류도 그리기를 통한 중등학교 지구과학 교사들의 동해해류에 대한 지식의 변화분석

이기영,박경애,박지은,최병주,이상호,김영택,이은일 한국지구과학회 2015 한국지구과학회지 Vol.36 No.3

The purpose of this study was to analyze the change of secondary earth science teachers’ knowledge about the currents of the East Sea through drawing of a schematic map of oceanic currents. For this purpose, thirty two earth science teachers participated in the six-hour long training of learning and practice related to ocean current schematic map. The teacher participants performed drawing of the ocean current schematic map of the East Sea in three different phases, i.e.; pre-, post-, and delayed-post phase. In addition, all the maps conducted by participants were converted to digitalized image data. Detailed analysis were performed to investigate participating teachers’ knowledge about the currents of the East Sea. Findings are as follows: First, the teacher participants have background knowledge about the ocean current map, but it reveals an incorrect knowledge about some concepts. Second, after teacher training, teachers’ knowledge increased about the East Sea’s currents, while a decrease was found in the differences between individual teachers’ knowledge. This pattern was more evident in the delayed-post phase of drawing than in the post-phase occurred immediately after training. Third, the teacher participants were strongly aware of the need to improve the ocean current schematic map of the East Sea in science textbook in terms of scientific knowledge. In addition, they showed a high level of satisfaction about teacher training because they perceived that it was meaningful in various aspects; recognizing the importance of content knowledge and conjunction with instructional strategies, the needs of secondary science curriculum, and recognition of the nature of scientific knowledge. The results imply that teachers’ subject matter knowledge plays a significant role to make science teaching effective. 이 연구의 목적은 해류 모식도 그리기를 통해 드러난 중등 지구과학 교사들의 동해 해류에 대한 지식의 변화를 분석하는 것이다 . 이를 위해 32명의 중등 지구과학 교사들이 총 6시간의 해류도 관련 학습과 실습 과정을 거쳤으며 , 사 전과 사후 그리고 지연된 사후 동해 해류 모식도 그리기를 수행하였다. 또한, 작성된 해류 모식도를 수치화 과정을 거 쳐 변환하여 이 해류 모식도에서 드러난 참여 교사들의 동해 해류에 대한 지식의 변화를 분석하였다 . 동해 해류에대 한 참여 교사들의 사전 지식을 분석한 결과 , 해류도에 대한 기초적인 지식은 가지고 있는 것으로 나타났으나 , 몇몇 개 념에 대해서는 잘못된 지식을 가진 것으로 분석되었다. 3차에 걸쳐 작성된 참여 교사들의 동해 해류 모식도를 분석한 결과, 연수 후 동해 해류 양상에 대한 지식이 증가하는 것으로 나타났으며 , 교사에 따른 차이는 감소하는 것으로 나타 났다. 이러한 경향은 연수 직후보다는 지연된 사후 단계에서 더욱 뚜렷하게 나타났다 . 해류도 실습활동에 대한 사후 설 문을 분석한 결과 , 참여 교사들은 해류도와 해류 교육의 필요성 , 과학적 지식에 근거한 교과서 해류도의 개선을 강하게 인식하고 있었다 . 또한, 실습활동에 대해 매우 높은 만족도를 나타내었으며 , 내용 지식의 중요성인식 및교수전략과 의 연계 , 중등 교육과정 개선의 필요 , 과학 지식의 본성에 대한 인식 등 다양한 측면에서 실습활동의 의미를 부여하였다. 이러한 결과는 교사의 교과내용학 지식이 효과적인 과학 교수에 중대한 역할을 함을 시사한다.

Case-based reasoning approach to cognitive map-driven tacit knowledge management

Lee, Kun Chang 성균관대학교 경영연구소 2000 Sungkyun Management Research Institute Work Vol.5 No.-

Knowledge is at the heart of knowledge management. In literature, a lot of studies have been suggested covering the role of knowledge in improving the performance of management. However, there are few studies about investigating knowledge itself in the arena of knowledge management. Knowledge circulating in an organization may be explicit or tacit. Until now, literature in knowledge management shows that it has mainly focused on explicit knowledge. On the other hand, tacit knowledge plays an important role in the success of knowledge management. It is relatively hard to formalize and reuse tacit knowledge. Therefore, research proposing the explication and reuse of tacit knowledge would contribute significantly to knowledge management research. In this sense, we propose using cognitive map as a main vehicle of formalizing tacit knowledge, and case-based reasoning as a tool for storing cognitive map-driven tacit knowledge in a form of frame-typed cases, and retrieving appropriate tacit knowledge from case base according to a new problem. Our proposed methodology was applied to a credit analysis problem in which decision-makers need tacit knowledge to assess whether a firm under consideration is healthy or not. Experiment results showed that our methodology for tacit knowledge management can provide decision makers with robust knowledge-based support.